{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Combined re-execution results\n",
    "\n",
    "This dataset combines results from R 3.2, 3.6 and 4.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib import rc\n",
    "import pandas as pd\n",
    "\n",
    "# plot style\n",
    "sns.set_style('whitegrid')\n",
    "sns.set_style({'font.family': 'Times New Roman'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load success rate data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_32_env = pd.read_csv(\"data/run_log_r32_env.csv\", sep=\"\\t\", names=[\"doi\", \"file\", \"r32\"])\n",
    "df_36_env = pd.read_csv(\"data/run_log_r36_env.csv\", sep=\"\\t\", names=[\"doi\", \"file\", \"r36\"])\n",
    "df_40_env = pd.read_csv(\"data/run_log_r40_env.csv\", sep=\"\\t\", names=[\"doi\", \"file\", \"r40\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "5028"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_32_env)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "6226\n"
    }
   ],
   "source": [
    "print(len(df_36_env))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "5288\n"
    }
   ],
   "source": [
    "print(len(df_40_env))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge results in one df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(df_32_env,df_36_env,on=['doi','file'], how='outer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "7129"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(df,df_40_env,on=['doi','file'], how='outer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "7621"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Combine results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "def get_combined_result(r):\n",
    "    if 'success' in [r.r32, r.r36, r.r40]:\n",
    "        return 'success'\n",
    "    if pd.isnull(r.r36) or pd.isnull(r.r32) or pd.isnull(r.r40):\n",
    "        return np.nan\n",
    "    if \"time limit exceeded\" in [r.r32, r.r36, r.r40]:\n",
    "        return np.nan\n",
    "    if \"not authorized\" in [r.r32, r.r36, r.r40]:\n",
    "        return 'auth'\n",
    "    if r.r36:\n",
    "        return r.r36\n",
    "    if r.r40:\n",
    "        return r.r40\n",
    "    if r.r32:\n",
    "        return r.r32\n",
    "\n",
    "df['result'] = df.apply(get_combined_result, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_success(el):\n",
    "    if pd.isna(el):\n",
    "        return el\n",
    "    if el == 'success':\n",
    "        return 1\n",
    "    if el == 'auth':\n",
    "        return -1\n",
    "    if len(str(el))>1:\n",
    "        return 0\n",
    "    else:\n",
    "        el\n",
    "\n",
    "df['success'] = df['result'].apply(get_success)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "NaN    3866\n0.0    2283\n1.0    1472\nName: success, dtype: int64"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['success'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "7621"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "2110"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.doi.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exclude bad DOIs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "er_362 = pd.read_csv(\"data/run_log_r36_env_download.csv\", sep=\"\\t\", names=[\"doi\", \"fileid\", \"status\"])\n",
    "er_322 = pd.read_csv(\"data/run_log_r32_env_download.csv\", sep=\"\\t\", names=[\"doi\", \"fileid\", \"status\"])\n",
    "er_402 = pd.read_csv(\"data/run_log_r40_env_download.csv\", sep=\"\\t\", names=[\"doi\", \"fileid\", \"status\"])\n",
    "\n",
    "error_data = [er_322, er_362, er_402]\n",
    "\n",
    "exclude = []\n",
    "for er in error_data:\n",
    "    temp = er[er.status != 'ok']\n",
    "    bad_dois = temp['doi'].unique().tolist()\n",
    "    exclude.append(set(bad_dois))\n",
    "    \n",
    "bad_dois = exclude[0] & exclude[1] & exclude[2] \n",
    "bad_dois = list(bad_dois)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(df[df.doi.isin(bad_dois) & (df['result'] != 'success')].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>doi</th>\n      <th>file</th>\n      <th>r32</th>\n      <th>r36</th>\n      <th>r40</th>\n      <th>result</th>\n      <th>success</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>doi:10.7910/DVN/XFQZI2</td>\n      <td>Condemnation.R</td>\n      <td>Error in eval(expr, envir, enclos) : could not...</td>\n      <td>Error in read.dta13('Condemnation.dta') :   co...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>doi:10.7910/DVN/WGPDBS</td>\n      <td>Replication_of_Figures.R</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_10_effect_of_winning_on_gov.R</td>\n      <td>Error in diag(vcovHC(DMareg, type = 'HC3')) : ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_11_rd_placebo.R</td>\n      <td>Error in ggsave('placebo.pdf', plot = placebo,...</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_12_historical_trend.R</td>\n      <td>Error in ggsave('historical_trend.pdf', plot =...</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                      doi                               file  \\\n0  doi:10.7910/DVN/XFQZI2                     Condemnation.R   \n1  doi:10.7910/DVN/WGPDBS           Replication_of_Figures.R   \n2  doi:10.7910/DVN/BPON3K  fig_10_effect_of_winning_on_gov.R   \n3  doi:10.7910/DVN/BPON3K                fig_11_rd_placebo.R   \n4  doi:10.7910/DVN/BPON3K          fig_12_historical_trend.R   \n\n                                                 r32  \\\n0  Error in eval(expr, envir, enclos) : could not...   \n1                                            success   \n2  Error in diag(vcovHC(DMareg, type = 'HC3')) : ...   \n3  Error in ggsave('placebo.pdf', plot = placebo,...   \n4  Error in ggsave('historical_trend.pdf', plot =...   \n\n                                                 r36  \\\n0  Error in read.dta13('Condemnation.dta') :   co...   \n1                                            success   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...   \n3                                            success   \n4                                            success   \n\n                                                 r40  \\\n0                                                NaN   \n1                                            success   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...   \n3                                            success   \n4                                            success   \n\n                                              result  success  \n0                                                NaN      NaN  \n1                                            success      1.0  \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...      0.0  \n3                                            success      1.0  \n4                                            success      1.0  "
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "7414"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "2085"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.doi.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('data/aggregate_results_env.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quick check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "Total number of entries: 3695\nTotal number after bad DOIs are removed: 3695\nUnique DOIs: 1447\nSuccess: 1472 out of 3695 => 0.3983761840324763\nTIL: 0 out of 3695 => 0.0\nError: 2223 out of 3695 => 0.6016238159675237\n"
    },
    {
     "data": {
      "image/png": "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\n",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Created with matplotlib (http://matplotlib.org/) -->\n<svg height=\"267.7275pt\" version=\"1.1\" viewBox=\"0 0 411.84 267.7275\" width=\"411.84pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <defs>\n  <style type=\"text/css\">\n*{stroke-linecap:butt;stroke-linejoin:round;}\n  </style>\n </defs>\n <g id=\"figure_1\">\n  <g id=\"patch_1\">\n   <path d=\"M 0 267.7275 \nL 411.84 267.7275 \nL 411.84 0 \nL 0 0 \nz\n\" style=\"fill:none;\"/>\n  </g>\n  <g id=\"axes_1\">\n   <g id=\"matplotlib.axis_1\"/>\n   <g id=\"matplotlib.axis_2\"/>\n   <g id=\"patch_2\">\n    <path d=\"M 284.631745 75.22533 \nC 274.1599 62.745471 260.873959 52.927497 245.869633 46.581109 \nC 230.865306 40.234722 214.566729 37.539318 198.318065 38.717191 \nC 182.069402 39.895064 166.329962 44.912919 152.397798 53.356925 \nC 138.465634 61.800932 126.734573 73.4324 118.172092 87.292067 \nC 109.609611 101.151733 104.457749 116.847821 103.141387 133.085851 \nC 101.825026 149.323882 104.381375 165.644847 110.599609 180.702736 \nC 116.817843 195.760624 126.522189 209.129787 138.912315 219.707652 \nC 151.302441 230.285516 166.02811 237.773073 181.874877 241.552812 \nL 205.761948 141.404948 \nL 284.631745 75.22533 \nz\n\" style=\"fill:#1f77b4;opacity:0.6;stroke:#ffffff;stroke-linejoin:miter;\"/>\n   </g>\n   <g id=\"patch_3\">\n    <path d=\"M 181.874877 241.552812 \nC 202.933535 246.575682 225.049417 244.830654 245.05974 236.567285 \nC 265.070063 228.303916 281.973189 213.935837 293.351809 195.517822 \nC 304.730429 177.099806 310.014974 155.553787 308.449704 133.961051 \nC 306.884434 112.368316 298.547699 91.809711 284.631733 75.225315 \nL 205.761948 141.404948 \nL 181.874877 241.552812 \nz\n\" style=\"fill:#ff7f0e;opacity:0.6;stroke:#ffffff;stroke-linejoin:miter;\"/>\n   </g>\n   <g id=\"patch_4\">\n    <path clip-path=\"url(#p96fadbedac)\" d=\"M 205.761948 213.474994 \nC 224.875148 213.474994 243.208093 205.88124 256.723166 192.366167 \nC 270.238239 178.851093 277.831994 160.518148 277.831994 141.404948 \nC 277.831994 122.291749 270.238239 103.958803 256.723166 90.44373 \nC 243.208093 76.928657 224.875148 69.334902 205.761948 69.334902 \nC 186.648748 69.334902 168.315803 76.928657 154.80073 90.44373 \nC 141.285656 103.958803 133.691902 122.291749 133.691902 141.404948 \nC 133.691902 160.518148 141.285656 178.851093 154.80073 192.366167 \nC 168.315803 205.88124 186.648748 213.474994 205.761948 213.474994 \nz\n\" style=\"fill:#ffffff;stroke:#ffffff;stroke-linejoin:miter;\"/>\n   </g>\n   <g id=\"text_1\">\n    <!-- Error -->\n    <defs>\n     <path d=\"M 20.90625 62.59375 \nL 20.90625 36.421875 \nL 35.453125 36.421875 \nQ 41.109375 36.421875 43.015625 38.140625 \nQ 45.5625 40.375 45.84375 46.046875 \nL 47.65625 46.046875 \nL 47.65625 23 \nL 45.84375 23 \nQ 45.171875 27.828125 44.484375 29.203125 \nQ 43.609375 30.90625 41.59375 31.875 \nQ 39.59375 32.859375 35.453125 32.859375 \nL 20.90625 32.859375 \nL 20.90625 11.03125 \nQ 20.90625 6.640625 21.296875 5.6875 \nQ 21.6875 4.734375 22.65625 4.171875 \nQ 23.640625 3.609375 26.375 3.609375 \nL 37.59375 3.609375 \nQ 43.21875 3.609375 45.75 4.390625 \nQ 48.296875 5.171875 50.640625 7.46875 \nQ 53.65625 10.5 56.84375 16.609375 \nL 58.796875 16.609375 \nL 53.078125 0 \nL 2.046875 0 \nL 2.046875 1.8125 \nL 4.390625 1.8125 \nQ 6.734375 1.8125 8.84375 2.9375 \nQ 10.40625 3.71875 10.96875 5.28125 \nQ 11.53125 6.84375 11.53125 11.671875 \nL 11.53125 54.6875 \nQ 11.53125 60.984375 10.25 62.453125 \nQ 8.5 64.40625 4.390625 64.40625 \nL 2.046875 64.40625 \nL 2.046875 66.21875 \nL 53.078125 66.21875 \nL 53.8125 51.703125 \nL 51.90625 51.703125 \nQ 50.875 56.9375 49.625 58.890625 \nQ 48.390625 60.84375 45.953125 61.859375 \nQ 44 62.59375 39.0625 62.59375 \nz\n\" id=\"TimesNewRomanPSMT-45\"/>\n     <path d=\"M 16.21875 46.046875 \nL 16.21875 35.984375 \nQ 21.828125 46.046875 27.734375 46.046875 \nQ 30.421875 46.046875 32.171875 44.40625 \nQ 33.9375 42.78125 33.9375 40.625 \nQ 33.9375 38.71875 32.65625 37.390625 \nQ 31.390625 36.078125 29.640625 36.078125 \nQ 27.9375 36.078125 25.8125 37.765625 \nQ 23.6875 39.453125 22.65625 39.453125 \nQ 21.78125 39.453125 20.75 38.484375 \nQ 18.5625 36.46875 16.21875 31.890625 \nL 16.21875 10.453125 \nQ 16.21875 6.734375 17.140625 4.828125 \nQ 17.78125 3.515625 19.390625 2.640625 \nQ 21 1.765625 24.03125 1.765625 \nL 24.03125 0 \nL 1.125 0 \nL 1.125 1.765625 \nQ 4.546875 1.765625 6.203125 2.828125 \nQ 7.421875 3.609375 7.90625 5.328125 \nQ 8.15625 6.15625 8.15625 10.0625 \nL 8.15625 27.390625 \nQ 8.15625 35.203125 7.828125 36.6875 \nQ 7.515625 38.1875 6.65625 38.859375 \nQ 5.8125 39.546875 4.546875 39.546875 \nQ 3.03125 39.546875 1.125 38.8125 \nL 0.640625 40.578125 \nL 14.15625 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-72\"/>\n     <path d=\"M 25 46.046875 \nQ 35.15625 46.046875 41.3125 38.328125 \nQ 46.53125 31.734375 46.53125 23.1875 \nQ 46.53125 17.1875 43.640625 11.03125 \nQ 40.765625 4.890625 35.71875 1.75 \nQ 30.671875 -1.375 24.46875 -1.375 \nQ 14.359375 -1.375 8.40625 6.6875 \nQ 3.375 13.484375 3.375 21.921875 \nQ 3.375 28.078125 6.421875 34.15625 \nQ 9.46875 40.234375 14.453125 43.140625 \nQ 19.4375 46.046875 25 46.046875 \nz\nM 23.484375 42.875 \nQ 20.90625 42.875 18.28125 41.328125 \nQ 15.671875 39.796875 14.0625 35.9375 \nQ 12.453125 32.078125 12.453125 26.03125 \nQ 12.453125 16.265625 16.328125 9.171875 \nQ 20.21875 2.09375 26.5625 2.09375 \nQ 31.296875 2.09375 34.375 6 \nQ 37.453125 9.90625 37.453125 19.4375 \nQ 37.453125 31.34375 32.328125 38.1875 \nQ 28.859375 42.875 23.484375 42.875 \nz\n\" id=\"TimesNewRomanPSMT-6f\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(75.658106 85.724529)scale(0.16 -0.16)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-45\"/>\n     <use x=\"61.083984\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"94.384766\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"127.685547\" xlink:href=\"#TimesNewRomanPSMT-6f\"/>\n     <use x=\"177.685547\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n    </g>\n   </g>\n   <g id=\"text_2\">\n    <!-- 60.16%  (2223) -->\n    <defs>\n     <path d=\"M 44.828125 67.578125 \nL 44.828125 65.765625 \nQ 38.375 65.140625 34.296875 63.203125 \nQ 30.21875 61.28125 26.234375 57.328125 \nQ 22.265625 53.375 19.65625 48.515625 \nQ 17.046875 43.65625 15.28125 36.96875 \nQ 22.3125 41.796875 29.390625 41.796875 \nQ 36.1875 41.796875 41.15625 36.328125 \nQ 46.140625 30.859375 46.140625 22.265625 \nQ 46.140625 13.96875 41.109375 7.125 \nQ 35.0625 -1.171875 25.09375 -1.171875 \nQ 18.3125 -1.171875 13.578125 3.328125 \nQ 4.296875 12.0625 4.296875 25.984375 \nQ 4.296875 34.859375 7.859375 42.859375 \nQ 11.421875 50.875 18.03125 57.078125 \nQ 24.65625 63.28125 30.703125 65.421875 \nQ 36.765625 67.578125 42 67.578125 \nz\nM 14.453125 33.40625 \nQ 13.578125 26.8125 13.578125 22.75 \nQ 13.578125 18.0625 15.3125 12.5625 \nQ 17.046875 7.078125 20.453125 3.859375 \nQ 22.953125 1.5625 26.515625 1.5625 \nQ 30.765625 1.5625 34.109375 5.5625 \nQ 37.453125 9.578125 37.453125 17 \nQ 37.453125 25.34375 34.125 31.4375 \nQ 30.8125 37.546875 24.703125 37.546875 \nQ 22.859375 37.546875 20.734375 36.765625 \nQ 18.609375 35.984375 14.453125 33.40625 \nz\n\" id=\"TimesNewRomanPSMT-36\"/>\n     <path d=\"M 3.609375 32.71875 \nQ 3.609375 44.046875 7.03125 52.21875 \nQ 10.453125 60.40625 16.109375 64.40625 \nQ 20.515625 67.578125 25.203125 67.578125 \nQ 32.8125 67.578125 38.875 59.8125 \nQ 46.4375 50.203125 46.4375 33.734375 \nQ 46.4375 22.21875 43.109375 14.15625 \nQ 39.796875 6.109375 34.640625 2.46875 \nQ 29.5 -1.171875 24.703125 -1.171875 \nQ 15.234375 -1.171875 8.9375 10.015625 \nQ 3.609375 19.4375 3.609375 32.71875 \nz\nM 13.1875 31.5 \nQ 13.1875 17.828125 16.546875 9.1875 \nQ 19.34375 1.90625 24.859375 1.90625 \nQ 27.484375 1.90625 30.3125 4.265625 \nQ 33.15625 6.640625 34.625 12.203125 \nQ 36.859375 20.609375 36.859375 35.890625 \nQ 36.859375 47.21875 34.515625 54.78125 \nQ 32.765625 60.40625 29.984375 62.75 \nQ 27.984375 64.359375 25.140625 64.359375 \nQ 21.828125 64.359375 19.234375 61.375 \nQ 15.71875 57.328125 14.453125 48.625 \nQ 13.1875 39.9375 13.1875 31.5 \nz\n\" id=\"TimesNewRomanPSMT-30\"/>\n     <path d=\"M 12.5 9.46875 \nQ 14.796875 9.46875 16.359375 7.875 \nQ 17.921875 6.296875 17.921875 4.046875 \nQ 17.921875 1.8125 16.328125 0.21875 \nQ 14.75 -1.375 12.5 -1.375 \nQ 10.25 -1.375 8.65625 0.21875 \nQ 7.078125 1.8125 7.078125 4.046875 \nQ 7.078125 6.34375 8.65625 7.90625 \nQ 10.25 9.46875 12.5 9.46875 \nz\n\" id=\"TimesNewRomanPSMT-2e\"/>\n     <path d=\"M 11.71875 59.71875 \nL 27.828125 67.578125 \nL 29.4375 67.578125 \nL 29.4375 11.671875 \nQ 29.4375 6.109375 29.90625 4.734375 \nQ 30.375 3.375 31.828125 2.640625 \nQ 33.296875 1.90625 37.796875 1.8125 \nL 37.796875 0 \nL 12.890625 0 \nL 12.890625 1.8125 \nQ 17.578125 1.90625 18.9375 2.609375 \nQ 20.3125 3.328125 20.84375 4.515625 \nQ 21.390625 5.71875 21.390625 11.671875 \nL 21.390625 47.40625 \nQ 21.390625 54.640625 20.90625 56.6875 \nQ 20.5625 58.25 19.65625 58.984375 \nQ 18.75 59.71875 17.484375 59.71875 \nQ 15.671875 59.71875 12.453125 58.203125 \nz\n\" id=\"TimesNewRomanPSMT-31\"/>\n     <path d=\"M 67.96875 67.71875 \nL 19.734375 -2.734375 \nL 15.375 -2.734375 \nL 63.625 67.71875 \nz\nM 17.78125 67.71875 \nQ 24.359375 67.71875 28 62.25 \nQ 31.640625 56.78125 31.640625 49.703125 \nQ 31.640625 41.21875 27.53125 36.578125 \nQ 23.4375 31.9375 17.671875 31.9375 \nQ 13.8125 31.9375 10.59375 34.0625 \nQ 7.375 36.1875 5.4375 40.375 \nQ 3.515625 44.578125 3.515625 49.703125 \nQ 3.515625 54.828125 5.46875 59.15625 \nQ 7.421875 63.484375 10.8125 65.59375 \nQ 14.203125 67.71875 17.78125 67.71875 \nz\nM 17.625 64.984375 \nQ 15.140625 64.984375 13.203125 62.046875 \nQ 11.28125 59.125 11.28125 49.75 \nQ 11.28125 42.96875 12.359375 39.40625 \nQ 13.1875 36.71875 14.9375 35.25 \nQ 15.96875 34.375 17.484375 34.375 \nQ 19.828125 34.375 21.484375 36.921875 \nQ 23.921875 40.671875 23.921875 49.46875 \nQ 23.921875 58.734375 21.53125 62.5 \nQ 19.96875 64.984375 17.625 64.984375 \nz\nM 65.71875 32.859375 \nQ 69.1875 32.859375 72.625 30.65625 \nQ 76.078125 28.46875 77.953125 24.265625 \nQ 79.828125 20.0625 79.828125 15.046875 \nQ 79.828125 6.390625 75.671875 1.828125 \nQ 71.53125 -2.734375 65.875 -2.734375 \nQ 62.3125 -2.734375 58.953125 -0.53125 \nQ 55.609375 1.65625 53.6875 5.734375 \nQ 51.765625 9.8125 51.765625 15.046875 \nQ 51.765625 20.171875 53.6875 24.40625 \nQ 55.609375 28.65625 58.953125 30.75 \nQ 62.3125 32.859375 65.71875 32.859375 \nz\nM 65.765625 30.28125 \nQ 63.421875 30.28125 61.71875 27.640625 \nQ 59.515625 24.21875 59.515625 14.703125 \nQ 59.515625 5.953125 61.765625 2.484375 \nQ 63.421875 0 65.765625 0 \nQ 68.015625 0 69.78125 2.6875 \nQ 72.125 6.25 72.125 14.9375 \nQ 72.125 24.125 69.78125 27.78125 \nQ 68.171875 30.28125 65.765625 30.28125 \nz\n\" id=\"TimesNewRomanPSMT-25\"/>\n     <path id=\"TimesNewRomanPSMT-20\"/>\n     <path d=\"M 31.0625 -19.578125 \nL 31.0625 -21.390625 \nQ 23.6875 -17.671875 18.75 -12.703125 \nQ 11.71875 -5.609375 7.90625 4 \nQ 4.109375 13.625 4.109375 23.96875 \nQ 4.109375 39.109375 11.578125 51.578125 \nQ 19.046875 64.0625 31.0625 69.4375 \nL 31.0625 67.390625 \nQ 25.046875 64.0625 21.1875 58.296875 \nQ 17.328125 52.546875 15.421875 43.703125 \nQ 13.53125 34.859375 13.53125 25.25 \nQ 13.53125 14.796875 15.140625 6.25 \nQ 16.40625 -0.484375 18.203125 -4.5625 \nQ 20.015625 -8.640625 23.0625 -12.390625 \nQ 26.125 -16.15625 31.0625 -19.578125 \nz\n\" id=\"TimesNewRomanPSMT-28\"/>\n     <path d=\"M 45.84375 12.75 \nL 41.21875 0 \nL 2.15625 0 \nL 2.15625 1.8125 \nQ 19.390625 17.53125 26.421875 27.484375 \nQ 33.453125 37.453125 33.453125 45.703125 \nQ 33.453125 52 29.59375 56.046875 \nQ 25.734375 60.109375 20.359375 60.109375 \nQ 15.484375 60.109375 11.59375 57.25 \nQ 7.71875 54.390625 5.859375 48.875 \nL 4.046875 48.875 \nQ 5.28125 57.90625 10.328125 62.734375 \nQ 15.375 67.578125 22.953125 67.578125 \nQ 31 67.578125 36.390625 62.40625 \nQ 41.796875 57.234375 41.796875 50.203125 \nQ 41.796875 45.171875 39.453125 40.140625 \nQ 35.84375 32.234375 27.734375 23.390625 \nQ 15.578125 10.109375 12.546875 7.375 \nL 29.828125 7.375 \nQ 35.109375 7.375 37.234375 7.765625 \nQ 39.359375 8.15625 41.0625 9.34375 \nQ 42.78125 10.546875 44.046875 12.75 \nz\n\" id=\"TimesNewRomanPSMT-32\"/>\n     <path d=\"M 5.078125 53.609375 \nQ 7.90625 60.296875 12.21875 63.9375 \nQ 16.546875 67.578125 23 67.578125 \nQ 30.953125 67.578125 35.203125 62.40625 \nQ 38.421875 58.546875 38.421875 54.15625 \nQ 38.421875 46.921875 29.34375 39.203125 \nQ 35.453125 36.8125 38.578125 32.375 \nQ 41.703125 27.9375 41.703125 21.921875 \nQ 41.703125 13.328125 36.234375 7.03125 \nQ 29.109375 -1.171875 15.578125 -1.171875 \nQ 8.890625 -1.171875 6.46875 0.484375 \nQ 4.046875 2.15625 4.046875 4.046875 \nQ 4.046875 5.46875 5.1875 6.546875 \nQ 6.34375 7.625 7.953125 7.625 \nQ 9.1875 7.625 10.453125 7.234375 \nQ 11.28125 6.984375 14.203125 5.4375 \nQ 17.140625 3.90625 18.265625 3.609375 \nQ 20.0625 3.078125 22.125 3.078125 \nQ 27.09375 3.078125 30.78125 6.9375 \nQ 34.46875 10.796875 34.46875 16.0625 \nQ 34.46875 19.921875 32.765625 23.578125 \nQ 31.5 26.3125 29.984375 27.734375 \nQ 27.875 29.6875 24.21875 31.265625 \nQ 20.5625 32.859375 16.75 32.859375 \nL 15.1875 32.859375 \nL 15.1875 34.328125 \nQ 19.046875 34.8125 22.921875 37.109375 \nQ 26.8125 39.40625 28.5625 42.625 \nQ 30.328125 45.84375 30.328125 49.703125 \nQ 30.328125 54.734375 27.171875 57.828125 \nQ 24.03125 60.9375 19.34375 60.9375 \nQ 11.765625 60.9375 6.6875 52.828125 \nz\n\" id=\"TimesNewRomanPSMT-33\"/>\n     <path d=\"M 2.25 67.390625 \nL 2.25 69.4375 \nQ 9.671875 65.765625 14.59375 60.796875 \nQ 21.578125 53.65625 25.390625 44.0625 \nQ 29.203125 34.46875 29.203125 24.078125 \nQ 29.203125 8.9375 21.75 -3.53125 \nQ 14.3125 -16.015625 2.25 -21.390625 \nL 2.25 -19.578125 \nQ 8.25 -16.21875 12.125 -10.46875 \nQ 16.015625 -4.734375 17.890625 4.125 \nQ 19.78125 12.984375 19.78125 22.609375 \nQ 19.78125 33.015625 18.171875 41.609375 \nQ 16.9375 48.34375 15.109375 52.390625 \nQ 13.28125 56.453125 10.25 60.203125 \nQ 7.234375 63.96875 2.25 67.390625 \nz\n\" id=\"TimesNewRomanPSMT-29\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(109.46569 112.300501)scale(0.14 -0.14)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-36\"/>\n     <use x=\"50\" xlink:href=\"#TimesNewRomanPSMT-30\"/>\n     <use x=\"100\" xlink:href=\"#TimesNewRomanPSMT-2e\"/>\n     <use x=\"125\" xlink:href=\"#TimesNewRomanPSMT-31\"/>\n     <use x=\"175\" xlink:href=\"#TimesNewRomanPSMT-36\"/>\n     <use x=\"225\" xlink:href=\"#TimesNewRomanPSMT-25\"/>\n     <use x=\"308.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"333.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"358.300781\" xlink:href=\"#TimesNewRomanPSMT-28\"/>\n     <use x=\"391.601562\" xlink:href=\"#TimesNewRomanPSMT-32\"/>\n     <use x=\"441.601562\" xlink:href=\"#TimesNewRomanPSMT-32\"/>\n     <use x=\"491.601562\" xlink:href=\"#TimesNewRomanPSMT-32\"/>\n     <use x=\"541.601562\" xlink:href=\"#TimesNewRomanPSMT-33\"/>\n     <use x=\"591.601562\" xlink:href=\"#TimesNewRomanPSMT-29\"/>\n    </g>\n   </g>\n   <g id=\"text_3\">\n    <!-- Success -->\n    <defs>\n     <path d=\"M 45.84375 67.71875 \nL 45.84375 44.828125 \nL 44.046875 44.828125 \nQ 43.171875 51.421875 40.890625 55.328125 \nQ 38.625 59.234375 34.421875 61.515625 \nQ 30.21875 63.8125 25.734375 63.8125 \nQ 20.65625 63.8125 17.328125 60.71875 \nQ 14.015625 57.625 14.015625 53.65625 \nQ 14.015625 50.640625 16.109375 48.140625 \nQ 19.140625 44.484375 30.515625 38.375 \nQ 39.796875 33.40625 43.1875 30.734375 \nQ 46.578125 28.078125 48.40625 24.453125 \nQ 50.25 20.84375 50.25 16.890625 \nQ 50.25 9.375 44.40625 3.921875 \nQ 38.578125 -1.515625 29.390625 -1.515625 \nQ 26.515625 -1.515625 23.96875 -1.078125 \nQ 22.46875 -0.828125 17.703125 0.703125 \nQ 12.9375 2.25 11.671875 2.25 \nQ 10.453125 2.25 9.734375 1.515625 \nQ 9.03125 0.78125 8.6875 -1.515625 \nL 6.890625 -1.515625 \nL 6.890625 21.1875 \nL 8.6875 21.1875 \nQ 9.96875 14.0625 12.109375 10.515625 \nQ 14.265625 6.984375 18.671875 4.640625 \nQ 23.09375 2.296875 28.375 2.296875 \nQ 34.46875 2.296875 38 5.515625 \nQ 41.546875 8.734375 41.546875 13.140625 \nQ 41.546875 15.578125 40.203125 18.0625 \nQ 38.875 20.5625 36.03125 22.703125 \nQ 34.125 24.171875 25.625 28.921875 \nQ 17.140625 33.6875 13.546875 36.515625 \nQ 9.96875 39.359375 8.109375 42.765625 \nQ 6.25 46.1875 6.25 50.296875 \nQ 6.25 57.421875 11.71875 62.5625 \nQ 17.1875 67.71875 25.640625 67.71875 \nQ 30.90625 67.71875 36.8125 65.140625 \nQ 39.546875 63.921875 40.671875 63.921875 \nQ 41.9375 63.921875 42.75 64.671875 \nQ 43.5625 65.4375 44.046875 67.71875 \nz\n\" id=\"TimesNewRomanPSMT-53\"/>\n     <path d=\"M 42.328125 44.734375 \nL 42.328125 17.625 \nQ 42.328125 9.859375 42.6875 8.125 \nQ 43.0625 6.390625 43.859375 5.703125 \nQ 44.671875 5.03125 45.75 5.03125 \nQ 47.265625 5.03125 49.171875 5.859375 \nL 49.859375 4.15625 \nL 36.46875 -1.375 \nL 34.28125 -1.375 \nL 34.28125 8.109375 \nQ 28.515625 1.859375 25.484375 0.234375 \nQ 22.46875 -1.375 19.09375 -1.375 \nQ 15.328125 -1.375 12.5625 0.796875 \nQ 9.8125 2.984375 8.734375 6.390625 \nQ 7.671875 9.8125 7.671875 16.0625 \nL 7.671875 36.03125 \nQ 7.671875 39.203125 6.984375 40.421875 \nQ 6.296875 41.65625 4.953125 42.3125 \nQ 3.609375 42.96875 0.09375 42.921875 \nL 0.09375 44.734375 \nL 15.765625 44.734375 \nL 15.765625 14.796875 \nQ 15.765625 8.546875 17.9375 6.59375 \nQ 20.125 4.640625 23.1875 4.640625 \nQ 25.296875 4.640625 27.953125 5.953125 \nQ 30.609375 7.28125 34.28125 10.984375 \nL 34.28125 36.328125 \nQ 34.28125 40.140625 32.890625 41.484375 \nQ 31.5 42.828125 27.09375 42.921875 \nL 27.09375 44.734375 \nz\n\" id=\"TimesNewRomanPSMT-75\"/>\n     <path d=\"M 41.109375 17 \nQ 39.3125 8.15625 34.03125 3.390625 \nQ 28.765625 -1.375 22.359375 -1.375 \nQ 14.75 -1.375 9.078125 5.015625 \nQ 3.421875 11.421875 3.421875 22.3125 \nQ 3.421875 32.859375 9.6875 39.453125 \nQ 15.96875 46.046875 24.75 46.046875 \nQ 31.34375 46.046875 35.59375 42.546875 \nQ 39.84375 39.0625 39.84375 35.296875 \nQ 39.84375 33.453125 38.640625 32.296875 \nQ 37.453125 31.15625 35.296875 31.15625 \nQ 32.421875 31.15625 30.953125 33.015625 \nQ 30.125 34.03125 29.859375 36.90625 \nQ 29.59375 39.796875 27.875 41.3125 \nQ 26.171875 42.78125 23.140625 42.78125 \nQ 18.265625 42.78125 15.28125 39.15625 \nQ 11.328125 34.375 11.328125 26.515625 \nQ 11.328125 18.5 15.25 12.375 \nQ 19.1875 6.25 25.875 6.25 \nQ 30.671875 6.25 34.46875 9.515625 \nQ 37.15625 11.765625 39.703125 17.671875 \nz\n\" id=\"TimesNewRomanPSMT-63\"/>\n     <path d=\"M 10.640625 27.875 \nQ 10.59375 17.921875 15.484375 12.25 \nQ 20.359375 6.59375 26.953125 6.59375 \nQ 31.34375 6.59375 34.59375 9 \nQ 37.84375 11.421875 40.046875 17.28125 \nL 41.546875 16.3125 \nQ 40.53125 9.625 35.59375 4.125 \nQ 30.671875 -1.375 23.25 -1.375 \nQ 15.1875 -1.375 9.453125 4.90625 \nQ 3.71875 11.1875 3.71875 21.78125 \nQ 3.71875 33.25 9.59375 39.671875 \nQ 15.484375 46.09375 24.359375 46.09375 \nQ 31.890625 46.09375 36.71875 41.140625 \nQ 41.546875 36.1875 41.546875 27.875 \nz\nM 10.640625 30.71875 \nL 31.34375 30.71875 \nQ 31.109375 35.015625 30.328125 36.765625 \nQ 29.109375 39.5 26.6875 41.0625 \nQ 24.265625 42.625 21.625 42.625 \nQ 17.578125 42.625 14.375 39.46875 \nQ 11.1875 36.328125 10.640625 30.71875 \nz\n\" id=\"TimesNewRomanPSMT-65\"/>\n     <path d=\"M 32.03125 46.046875 \nL 32.03125 30.8125 \nL 30.421875 30.8125 \nQ 28.5625 37.984375 25.65625 40.578125 \nQ 22.75 43.171875 18.265625 43.171875 \nQ 14.84375 43.171875 12.734375 41.359375 \nQ 10.640625 39.546875 10.640625 37.359375 \nQ 10.640625 34.625 12.203125 32.671875 \nQ 13.71875 30.671875 18.359375 28.421875 \nL 25.484375 24.953125 \nQ 35.40625 20.125 35.40625 12.203125 \nQ 35.40625 6.109375 30.78125 2.359375 \nQ 26.171875 -1.375 20.453125 -1.375 \nQ 16.359375 -1.375 11.078125 0.09375 \nQ 9.46875 0.59375 8.453125 0.59375 \nQ 7.328125 0.59375 6.6875 -0.6875 \nL 5.078125 -0.6875 \nL 5.078125 15.28125 \nL 6.6875 15.28125 \nQ 8.0625 8.453125 11.90625 4.984375 \nQ 15.765625 1.515625 20.5625 1.515625 \nQ 23.921875 1.515625 26.046875 3.484375 \nQ 28.171875 5.46875 28.171875 8.25 \nQ 28.171875 11.625 25.796875 13.921875 \nQ 23.4375 16.21875 16.359375 19.734375 \nQ 9.28125 23.25 7.078125 26.078125 \nQ 4.890625 28.859375 4.890625 33.109375 \nQ 4.890625 38.625 8.671875 42.328125 \nQ 12.453125 46.046875 18.453125 46.046875 \nQ 21.09375 46.046875 24.859375 44.921875 \nQ 27.34375 44.1875 28.171875 44.1875 \nQ 28.953125 44.1875 29.390625 44.53125 \nQ 29.828125 44.875 30.421875 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-73\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(302.110795 204.772859)scale(0.16 -0.16)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-53\"/>\n     <use x=\"55.615234\" xlink:href=\"#TimesNewRomanPSMT-75\"/>\n     <use x=\"105.615234\" xlink:href=\"#TimesNewRomanPSMT-63\"/>\n     <use x=\"150\" xlink:href=\"#TimesNewRomanPSMT-63\"/>\n     <use x=\"194.384766\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"238.769531\" xlink:href=\"#TimesNewRomanPSMT-73\"/>\n     <use x=\"277.685547\" xlink:href=\"#TimesNewRomanPSMT-73\"/>\n    </g>\n   </g>\n   <g id=\"text_4\">\n    <!-- 39.84%  (1472) -->\n    <defs>\n     <path d=\"M 5.28125 -1.375 \nL 5.28125 0.4375 \nQ 11.625 0.53125 17.09375 3.390625 \nQ 22.5625 6.25 27.65625 13.375 \nQ 32.765625 20.515625 34.765625 29.046875 \nQ 27.09375 24.125 20.90625 24.125 \nQ 13.921875 24.125 8.9375 29.515625 \nQ 3.953125 34.90625 3.953125 43.84375 \nQ 3.953125 52.546875 8.9375 59.328125 \nQ 14.9375 67.578125 24.609375 67.578125 \nQ 32.765625 67.578125 38.578125 60.84375 \nQ 45.703125 52.484375 45.703125 40.234375 \nQ 45.703125 29.203125 40.28125 19.65625 \nQ 34.859375 10.109375 25.203125 3.8125 \nQ 17.328125 -1.375 8.0625 -1.375 \nz\nM 35.546875 32.671875 \nQ 36.421875 39.015625 36.421875 42.828125 \nQ 36.421875 47.5625 34.8125 53.046875 \nQ 33.203125 58.546875 30.25 61.46875 \nQ 27.296875 64.40625 23.53125 64.40625 \nQ 19.1875 64.40625 15.90625 60.5 \nQ 12.640625 56.59375 12.640625 48.875 \nQ 12.640625 38.578125 17 32.765625 \nQ 20.171875 28.5625 24.8125 28.5625 \nQ 27.046875 28.5625 30.125 29.640625 \nQ 33.203125 30.71875 35.546875 32.671875 \nz\n\" id=\"TimesNewRomanPSMT-39\"/>\n     <path d=\"M 19.1875 33.34375 \nQ 11.328125 39.796875 9.046875 43.703125 \nQ 6.78125 47.609375 6.78125 51.8125 \nQ 6.78125 58.25 11.765625 62.90625 \nQ 16.75 67.578125 25 67.578125 \nQ 33.015625 67.578125 37.890625 63.234375 \nQ 42.78125 58.890625 42.78125 53.328125 \nQ 42.78125 49.609375 40.140625 45.75 \nQ 37.5 41.890625 29.15625 36.671875 \nQ 37.75 30.03125 40.53125 26.21875 \nQ 44.234375 21.234375 44.234375 15.71875 \nQ 44.234375 8.734375 38.90625 3.78125 \nQ 33.59375 -1.171875 24.953125 -1.171875 \nQ 15.53125 -1.171875 10.25 4.734375 \nQ 6.0625 9.46875 6.0625 15.09375 \nQ 6.0625 19.484375 9.015625 23.796875 \nQ 11.96875 28.125 19.1875 33.34375 \nz\nM 26.859375 38.578125 \nQ 32.71875 43.84375 34.28125 46.890625 \nQ 35.84375 49.953125 35.84375 53.8125 \nQ 35.84375 58.9375 32.953125 61.84375 \nQ 30.078125 64.75 25.09375 64.75 \nQ 20.125 64.75 17 61.859375 \nQ 13.875 58.984375 13.875 55.125 \nQ 13.875 52.59375 15.15625 50.046875 \nQ 16.453125 47.515625 18.84375 45.21875 \nz\nM 21.484375 31.5 \nQ 17.4375 28.078125 15.484375 24.046875 \nQ 13.53125 20.015625 13.53125 15.328125 \nQ 13.53125 9.03125 16.96875 5.25 \nQ 20.40625 1.46875 25.734375 1.46875 \nQ 31 1.46875 34.171875 4.4375 \nQ 37.359375 7.421875 37.359375 11.671875 \nQ 37.359375 15.1875 35.5 17.96875 \nQ 32.03125 23.140625 21.484375 31.5 \nz\n\" id=\"TimesNewRomanPSMT-38\"/>\n     <path d=\"M 46.53125 24.421875 \nL 46.53125 17.484375 \nL 37.640625 17.484375 \nL 37.640625 0 \nL 29.59375 0 \nL 29.59375 17.484375 \nL 1.5625 17.484375 \nL 1.5625 23.734375 \nL 32.28125 67.578125 \nL 37.640625 67.578125 \nL 37.640625 24.421875 \nz\nM 29.59375 24.421875 \nL 29.59375 57.28125 \nL 6.34375 24.421875 \nz\n\" id=\"TimesNewRomanPSMT-34\"/>\n     <path d=\"M 10.0625 66.21875 \nL 45.5625 66.21875 \nL 45.5625 64.359375 \nL 23.484375 -1.375 \nL 18.015625 -1.375 \nL 37.796875 58.25 \nL 19.578125 58.25 \nQ 14.0625 58.25 11.71875 56.9375 \nQ 7.625 54.6875 5.125 50 \nL 3.71875 50.53125 \nz\n\" id=\"TimesNewRomanPSMT-37\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(214.573521 177.235953)scale(0.14 -0.14)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-33\"/>\n     <use x=\"50\" xlink:href=\"#TimesNewRomanPSMT-39\"/>\n     <use x=\"100\" xlink:href=\"#TimesNewRomanPSMT-2e\"/>\n     <use x=\"125\" xlink:href=\"#TimesNewRomanPSMT-38\"/>\n     <use x=\"175\" xlink:href=\"#TimesNewRomanPSMT-34\"/>\n     <use x=\"225\" xlink:href=\"#TimesNewRomanPSMT-25\"/>\n     <use x=\"308.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"333.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"358.300781\" xlink:href=\"#TimesNewRomanPSMT-28\"/>\n     <use x=\"391.601562\" xlink:href=\"#TimesNewRomanPSMT-31\"/>\n     <use x=\"441.601562\" xlink:href=\"#TimesNewRomanPSMT-34\"/>\n     <use x=\"491.601562\" xlink:href=\"#TimesNewRomanPSMT-37\"/>\n     <use x=\"541.601562\" xlink:href=\"#TimesNewRomanPSMT-32\"/>\n     <use x=\"591.601562\" xlink:href=\"#TimesNewRomanPSMT-29\"/>\n    </g>\n   </g>\n   <g id=\"text_5\">\n    <!-- Total re-execution rate per file -->\n    <defs>\n     <path d=\"M 57.859375 66.21875 \nL 58.59375 50.6875 \nL 56.734375 50.6875 \nQ 56.203125 54.78125 55.28125 56.546875 \nQ 53.765625 59.375 51.25 60.71875 \nQ 48.734375 62.0625 44.625 62.0625 \nL 35.296875 62.0625 \nL 35.296875 11.46875 \nQ 35.296875 5.375 36.625 3.859375 \nQ 38.484375 1.8125 42.328125 1.8125 \nL 44.625 1.8125 \nL 44.625 0 \nL 16.546875 0 \nL 16.546875 1.8125 \nL 18.890625 1.8125 \nQ 23.09375 1.8125 24.859375 4.34375 \nQ 25.921875 5.90625 25.921875 11.46875 \nL 25.921875 62.0625 \nL 17.96875 62.0625 \nQ 13.328125 62.0625 11.375 61.375 \nQ 8.84375 60.453125 7.03125 57.8125 \nQ 5.21875 55.171875 4.890625 50.6875 \nL 3.03125 50.6875 \nL 3.8125 66.21875 \nz\n\" id=\"TimesNewRomanPSMT-54\"/>\n     <path d=\"M 16.109375 59.421875 \nL 16.109375 44.734375 \nL 26.5625 44.734375 \nL 26.5625 41.3125 \nL 16.109375 41.3125 \nL 16.109375 12.3125 \nQ 16.109375 7.953125 17.359375 6.4375 \nQ 18.609375 4.9375 20.5625 4.9375 \nQ 22.171875 4.9375 23.6875 5.9375 \nQ 25.203125 6.9375 26.03125 8.890625 \nL 27.9375 8.890625 \nQ 26.21875 4.109375 23.09375 1.6875 \nQ 19.96875 -0.734375 16.65625 -0.734375 \nQ 14.40625 -0.734375 12.25 0.515625 \nQ 10.109375 1.765625 9.078125 4.078125 \nQ 8.0625 6.390625 8.0625 11.234375 \nL 8.0625 41.3125 \nL 0.984375 41.3125 \nL 0.984375 42.921875 \nQ 3.65625 44 6.46875 46.5625 \nQ 9.28125 49.125 11.46875 52.640625 \nQ 12.59375 54.5 14.59375 59.421875 \nz\n\" id=\"TimesNewRomanPSMT-74\"/>\n     <path d=\"M 28.46875 6.453125 \nQ 21.578125 1.125 19.828125 0.296875 \nQ 17.1875 -0.921875 14.203125 -0.921875 \nQ 9.578125 -0.921875 6.5625 2.25 \nQ 3.5625 5.421875 3.5625 10.59375 \nQ 3.5625 13.875 5.03125 16.265625 \nQ 7.03125 19.578125 11.984375 22.5 \nQ 16.9375 25.4375 28.46875 29.640625 \nL 28.46875 31.390625 \nQ 28.46875 38.09375 26.34375 40.578125 \nQ 24.21875 43.0625 20.171875 43.0625 \nQ 17.09375 43.0625 15.28125 41.40625 \nQ 13.421875 39.75 13.421875 37.59375 \nL 13.53125 34.765625 \nQ 13.53125 32.515625 12.375 31.296875 \nQ 11.234375 30.078125 9.375 30.078125 \nQ 7.5625 30.078125 6.421875 31.34375 \nQ 5.28125 32.625 5.28125 34.8125 \nQ 5.28125 39.015625 9.578125 42.53125 \nQ 13.875 46.046875 21.625 46.046875 \nQ 27.59375 46.046875 31.390625 44.046875 \nQ 34.28125 42.53125 35.640625 39.3125 \nQ 36.53125 37.203125 36.53125 30.71875 \nL 36.53125 15.53125 \nQ 36.53125 9.125 36.765625 7.6875 \nQ 37.015625 6.25 37.578125 5.765625 \nQ 38.140625 5.28125 38.875 5.28125 \nQ 39.65625 5.28125 40.234375 5.609375 \nQ 41.265625 6.25 44.1875 9.1875 \nL 44.1875 6.453125 \nQ 38.71875 -0.875 33.734375 -0.875 \nQ 31.34375 -0.875 29.921875 0.78125 \nQ 28.515625 2.4375 28.46875 6.453125 \nz\nM 28.46875 9.625 \nL 28.46875 26.65625 \nQ 21.09375 23.734375 18.953125 22.515625 \nQ 15.09375 20.359375 13.421875 18.015625 \nQ 11.765625 15.671875 11.765625 12.890625 \nQ 11.765625 9.375 13.859375 7.046875 \nQ 15.96875 4.734375 18.703125 4.734375 \nQ 22.40625 4.734375 28.46875 9.625 \nz\n\" id=\"TimesNewRomanPSMT-61\"/>\n     <path d=\"M 18.5 69.4375 \nL 18.5 10.109375 \nQ 18.5 5.90625 19.109375 4.53125 \nQ 19.734375 3.171875 21 2.46875 \nQ 22.265625 1.765625 25.734375 1.765625 \nL 25.734375 0 \nL 3.8125 0 \nL 3.8125 1.765625 \nQ 6.890625 1.765625 8 2.390625 \nQ 9.125 3.03125 9.765625 4.484375 \nQ 10.40625 5.953125 10.40625 10.109375 \nL 10.40625 50.734375 \nQ 10.40625 58.296875 10.0625 60.03125 \nQ 9.71875 61.765625 8.953125 62.390625 \nQ 8.203125 63.03125 7.03125 63.03125 \nQ 5.765625 63.03125 3.8125 62.25 \nL 2.984375 63.96875 \nL 16.3125 69.4375 \nz\n\" id=\"TimesNewRomanPSMT-6c\"/>\n     <path d=\"M 4.046875 26.125 \nL 29.296875 26.125 \nL 29.296875 18.75 \nL 4.046875 18.75 \nz\n\" id=\"TimesNewRomanPSMT-2d\"/>\n     <path d=\"M 1.3125 44.734375 \nL 22.359375 44.734375 \nL 22.359375 42.921875 \nQ 20.359375 42.921875 19.546875 42.234375 \nQ 18.75 41.546875 18.75 40.4375 \nQ 18.75 39.265625 20.453125 36.8125 \nQ 21 36.03125 22.078125 34.375 \nL 25.25 29.296875 \nL 28.90625 34.375 \nQ 32.421875 39.203125 32.421875 40.484375 \nQ 32.421875 41.5 31.59375 42.203125 \nQ 30.765625 42.921875 28.90625 42.921875 \nL 28.90625 44.734375 \nL 44.046875 44.734375 \nL 44.046875 42.921875 \nQ 41.65625 42.78125 39.890625 41.609375 \nQ 37.5 39.9375 33.34375 34.375 \nL 27.25 26.21875 \nL 38.375 10.203125 \nQ 42.484375 4.296875 44.234375 3.09375 \nQ 46 1.90625 48.78125 1.765625 \nL 48.78125 0 \nL 27.6875 0 \nL 27.6875 1.765625 \nQ 29.890625 1.765625 31.109375 2.734375 \nQ 32.03125 3.421875 32.03125 4.546875 \nQ 32.03125 5.671875 28.90625 10.203125 \nL 22.359375 19.78125 \nL 15.1875 10.203125 \nQ 11.859375 5.765625 11.859375 4.9375 \nQ 11.859375 3.765625 12.953125 2.8125 \nQ 14.0625 1.859375 16.265625 1.765625 \nL 16.265625 0 \nL 1.65625 0 \nL 1.65625 1.765625 \nQ 3.421875 2 4.734375 2.984375 \nQ 6.59375 4.390625 10.984375 10.203125 \nL 20.359375 22.65625 \nL 11.859375 34.96875 \nQ 8.25 40.234375 6.265625 41.578125 \nQ 4.296875 42.921875 1.3125 42.921875 \nz\n\" id=\"TimesNewRomanPSMT-78\"/>\n     <path d=\"M 14.5 69.4375 \nQ 16.546875 69.4375 17.984375 67.984375 \nQ 19.4375 66.546875 19.4375 64.5 \nQ 19.4375 62.453125 17.984375 60.984375 \nQ 16.546875 59.515625 14.5 59.515625 \nQ 12.453125 59.515625 10.984375 60.984375 \nQ 9.515625 62.453125 9.515625 64.5 \nQ 9.515625 66.546875 10.953125 67.984375 \nQ 12.40625 69.4375 14.5 69.4375 \nz\nM 18.5625 46.046875 \nL 18.5625 10.109375 \nQ 18.5625 5.90625 19.171875 4.515625 \nQ 19.78125 3.125 20.96875 2.4375 \nQ 22.171875 1.765625 25.34375 1.765625 \nL 25.34375 0 \nL 3.609375 0 \nL 3.609375 1.765625 \nQ 6.890625 1.765625 8 2.390625 \nQ 9.125 3.03125 9.78125 4.484375 \nQ 10.453125 5.953125 10.453125 10.109375 \nL 10.453125 27.34375 \nQ 10.453125 34.625 10.015625 36.765625 \nQ 9.671875 38.328125 8.9375 38.9375 \nQ 8.203125 39.546875 6.9375 39.546875 \nQ 5.5625 39.546875 3.609375 38.8125 \nL 2.9375 40.578125 \nL 16.40625 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-69\"/>\n     <path d=\"M 16.15625 36.578125 \nQ 24.03125 46.046875 31.15625 46.046875 \nQ 34.8125 46.046875 37.453125 44.21875 \nQ 40.09375 42.390625 41.65625 38.1875 \nQ 42.71875 35.25 42.71875 29.203125 \nL 42.71875 10.109375 \nQ 42.71875 5.859375 43.40625 4.34375 \nQ 43.953125 3.125 45.140625 2.4375 \nQ 46.34375 1.765625 49.5625 1.765625 \nL 49.5625 0 \nL 27.4375 0 \nL 27.4375 1.765625 \nL 28.375 1.765625 \nQ 31.5 1.765625 32.734375 2.703125 \nQ 33.984375 3.65625 34.46875 5.515625 \nQ 34.671875 6.25 34.671875 10.109375 \nL 34.671875 28.421875 \nQ 34.671875 34.515625 33.078125 37.28125 \nQ 31.5 40.046875 27.734375 40.046875 \nQ 21.921875 40.046875 16.15625 33.6875 \nL 16.15625 10.109375 \nQ 16.15625 5.5625 16.703125 4.5 \nQ 17.390625 3.078125 18.578125 2.421875 \nQ 19.78125 1.765625 23.4375 1.765625 \nL 23.4375 0 \nL 1.3125 0 \nL 1.3125 1.765625 \nL 2.296875 1.765625 \nQ 5.71875 1.765625 6.90625 3.484375 \nQ 8.109375 5.21875 8.109375 10.109375 \nL 8.109375 26.703125 \nQ 8.109375 34.765625 7.734375 36.515625 \nQ 7.375 38.28125 6.609375 38.90625 \nQ 5.859375 39.546875 4.59375 39.546875 \nQ 3.21875 39.546875 1.3125 38.8125 \nL 0.59375 40.578125 \nL 14.0625 46.046875 \nL 16.15625 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-6e\"/>\n     <path d=\"M -0.09375 40.28125 \nL 13.671875 45.84375 \nL 15.53125 45.84375 \nL 15.53125 35.40625 \nQ 19 41.3125 22.484375 43.671875 \nQ 25.984375 46.046875 29.828125 46.046875 \nQ 36.578125 46.046875 41.0625 40.765625 \nQ 46.578125 34.328125 46.578125 23.96875 \nQ 46.578125 12.40625 39.9375 4.828125 \nQ 34.46875 -1.375 26.171875 -1.375 \nQ 22.5625 -1.375 19.921875 -0.34375 \nQ 17.96875 0.390625 15.53125 2.59375 \nL 15.53125 -11.03125 \nQ 15.53125 -15.625 16.09375 -16.859375 \nQ 16.65625 -18.109375 18.046875 -18.84375 \nQ 19.4375 -19.578125 23.09375 -19.578125 \nL 23.09375 -21.390625 \nL -0.34375 -21.390625 \nL -0.34375 -19.578125 \nL 0.875 -19.578125 \nQ 3.5625 -19.625 5.46875 -18.5625 \nQ 6.390625 -18.015625 6.90625 -16.8125 \nQ 7.421875 -15.625 7.421875 -10.75 \nL 7.421875 31.546875 \nQ 7.421875 35.890625 7.03125 37.0625 \nQ 6.640625 38.234375 5.78125 38.8125 \nQ 4.9375 39.40625 3.46875 39.40625 \nQ 2.296875 39.40625 0.484375 38.71875 \nz\nM 15.53125 32.515625 \nL 15.53125 15.828125 \nQ 15.53125 10.40625 15.96875 8.6875 \nQ 16.65625 5.859375 19.3125 3.703125 \nQ 21.96875 1.5625 26.03125 1.5625 \nQ 30.90625 1.5625 33.9375 5.375 \nQ 37.890625 10.359375 37.890625 19.390625 \nQ 37.890625 29.640625 33.40625 35.15625 \nQ 30.28125 38.96875 25.984375 38.96875 \nQ 23.640625 38.96875 21.34375 37.796875 \nQ 19.578125 36.921875 15.53125 32.515625 \nz\n\" id=\"TimesNewRomanPSMT-70\"/>\n     <path d=\"M 20.609375 41.21875 \nL 20.609375 11.8125 \nQ 20.609375 5.5625 21.96875 3.90625 \nQ 23.78125 1.765625 26.8125 1.765625 \nL 30.859375 1.765625 \nL 30.859375 0 \nL 4.15625 0 \nL 4.15625 1.765625 \nL 6.15625 1.765625 \nQ 8.109375 1.765625 9.71875 2.734375 \nQ 11.328125 3.71875 11.9375 5.375 \nQ 12.546875 7.03125 12.546875 11.8125 \nL 12.546875 41.21875 \nL 3.859375 41.21875 \nL 3.859375 44.734375 \nL 12.546875 44.734375 \nL 12.546875 47.65625 \nQ 12.546875 54.34375 14.6875 58.984375 \nQ 16.84375 63.625 21.265625 66.484375 \nQ 25.6875 69.34375 31.203125 69.34375 \nQ 36.328125 69.34375 40.625 66.015625 \nQ 43.453125 63.8125 43.453125 61.078125 \nQ 43.453125 59.625 42.1875 58.328125 \nQ 40.921875 57.03125 39.453125 57.03125 \nQ 38.328125 57.03125 37.078125 57.828125 \nQ 35.84375 58.640625 34.03125 61.296875 \nQ 32.234375 63.96875 30.71875 64.890625 \nQ 29.203125 65.828125 27.34375 65.828125 \nQ 25.09375 65.828125 23.53125 64.625 \nQ 21.96875 63.421875 21.28125 60.90625 \nQ 20.609375 58.40625 20.609375 47.953125 \nL 20.609375 44.734375 \nL 32.125 44.734375 \nL 32.125 41.21875 \nz\n\" id=\"TimesNewRomanPSMT-66\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(83.77625 21.0875)scale(0.2 -0.2)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-54\"/>\n     <use x=\"60.974609\" xlink:href=\"#TimesNewRomanPSMT-6f\"/>\n     <use x=\"110.974609\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n     <use x=\"138.757812\" xlink:href=\"#TimesNewRomanPSMT-61\"/>\n     <use x=\"183.142578\" xlink:href=\"#TimesNewRomanPSMT-6c\"/>\n     <use x=\"210.925781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"235.925781\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"269.226562\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"313.611328\" xlink:href=\"#TimesNewRomanPSMT-2d\"/>\n     <use x=\"346.912109\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"391.296875\" xlink:href=\"#TimesNewRomanPSMT-78\"/>\n     <use x=\"441.296875\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"485.681641\" xlink:href=\"#TimesNewRomanPSMT-63\"/>\n     <use x=\"530.066406\" xlink:href=\"#TimesNewRomanPSMT-75\"/>\n     <use x=\"580.066406\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n     <use x=\"607.849609\" xlink:href=\"#TimesNewRomanPSMT-69\"/>\n     <use x=\"635.632812\" xlink:href=\"#TimesNewRomanPSMT-6f\"/>\n     <use x=\"685.632812\" xlink:href=\"#TimesNewRomanPSMT-6e\"/>\n     <use x=\"735.632812\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"760.632812\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"793.933594\" xlink:href=\"#TimesNewRomanPSMT-61\"/>\n     <use x=\"838.318359\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n     <use x=\"866.101562\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"910.486328\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"935.486328\" xlink:href=\"#TimesNewRomanPSMT-70\"/>\n     <use x=\"985.486328\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"1029.871094\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"1063.171875\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"1088.171875\" xlink:href=\"#TimesNewRomanPSMT-66\"/>\n     <use x=\"1121.472656\" xlink:href=\"#TimesNewRomanPSMT-69\"/>\n     <use x=\"1149.255859\" xlink:href=\"#TimesNewRomanPSMT-6c\"/>\n     <use x=\"1177.039062\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n    </g>\n   </g>\n  </g>\n </g>\n <defs>\n  <clipPath id=\"p96fadbedac\">\n   <rect height=\"229.94\" width=\"390.44\" x=\"10.7\" y=\"27.0875\"/>\n  </clipPath>\n </defs>\n</svg>\n",
      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def make_autopct(values):\n",
    "    def my_autopct(pct):\n",
    "        total = sum(values)\n",
    "        val = int(round(pct*total/100.0))\n",
    "        return '{p:.2f}%  ({v:d})'.format(p=pct,v=val)\n",
    "    return my_autopct\n",
    "\n",
    "def get_success_rates(df):\n",
    "    print \"Total number of entries: \"+ str(len(df))\n",
    "    print \"Total number after bad DOIs are removed: \"+ str(len(df))\n",
    "    \n",
    "    print \"Unique DOIs: \"+ str(len(df['doi'].unique()))\n",
    "    \n",
    "    # calculate success\n",
    "    success = (df['result'] == 'success').sum()\n",
    "    print \"Success: \" + str(success)+ \" out of \" + str(len(df)) +\" => \"+ str(success*1.0/len(df))\n",
    "    \n",
    "    til = (df['result'] == 'time limit exceeded').sum()\n",
    "    print \"TIL: \" + str(til)+ \" out of \" + str(len(df)) +\" => \"+ str(til*1.0/len(df))\n",
    "    \n",
    "    error = len(df)-til-success\n",
    "    print \"Error: \" + str(error)+ \" out of \" + str(len(df)) +\" => \"+ str(error*1.0/len(df))\n",
    "    \n",
    "    return [error, success]\n",
    "\n",
    "def plot_code(df, plot_title, plot_name, aggregation=False):\n",
    "    labels = ['Error', 'Success']\n",
    "    if aggregation:\n",
    "        sizes = get_aggregated(df)\n",
    "    else:\n",
    "        sizes = get_success_rates(df)\n",
    "     \n",
    "    fig1, ax1 = plt.subplots()\n",
    "    plt.rcParams['font.size'] = 16\n",
    "    ax1.pie(sizes, labels=labels, autopct=make_autopct(sizes), startangle=40,  \\\n",
    "            textprops={'fontsize': 14},wedgeprops={'alpha':0.6})\n",
    "\n",
    "    #draw circle\n",
    "    centre_circle = plt.Circle((0,0),0.70,fc='white')\n",
    "\n",
    "    fig = plt.gcf()\n",
    "    fig.gca().add_artist(centre_circle)\n",
    "\n",
    "    # Equal aspect ratio ensures that pie is drawn as a circle\n",
    "    ax1.axis('equal')  \n",
    "    plt.title(plot_title, size=20)\n",
    "    plt.tight_layout()\n",
    "\n",
    "    plt.show()\n",
    "    fig1.savefig(\"plots/{}\".format(plot_name), dpi=100)\n",
    "    \n",
    "dfe = df[df.result.notnull()]\n",
    "plot_code(dfe, \"Total re-execution rate per file\", \"aggregated_env.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Same for `no env` data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_32_env = pd.read_csv(\"data/run_log_r32_no_env.csv\", sep=\"\\t\", names=[\"doi\", \"file\", \"r32\"])\n",
    "df_36_env = pd.read_csv(\"data/run_log_r36_no_env.csv\", sep=\"\\t\", names=[\"doi\", \"file\", \"r36\"])\n",
    "df_40_env = pd.read_csv(\"data/run_log_r40_no_env.csv\", sep=\"\\t\", names=[\"doi\", \"file\", \"r40\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "7088"
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_32_env)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "4042\n"
    }
   ],
   "source": [
    "print(len(df_36_env))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "7149\n"
    }
   ],
   "source": [
    "print(len(df_40_env))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge results in one df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(df_32_env,df_36_env,on=['doi','file'], how='outer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "7310"
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(df,df_40_env,on=['doi','file'], how='outer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "7985"
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Combine results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['result'] = df.apply(get_combined_result, axis=1)\n",
    "df['success'] = df['result'].apply(get_success)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>doi</th>\n      <th>file</th>\n      <th>r32</th>\n      <th>r36</th>\n      <th>r40</th>\n      <th>result</th>\n      <th>success</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>doi:10.7910/DVN/XFQZI2</td>\n      <td>Condemnation.R</td>\n      <td>Error in library(readstata13) : there is no pa...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>doi:10.7910/DVN/WGPDBS</td>\n      <td>Replication_of_Figures.R</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_10_effect_of_winning_on_gov.R</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_11_rd_placebo.R</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_12_historical_trend.R</td>\n      <td>Error in library(ggthemes) : there is no packa...</td>\n      <td>NaN</td>\n      <td>Error in library(ggthemes) : there is no packa...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_13_plot_loyalty_df_pct.R</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_14_effect_on_individual_parties.R</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_2_fig_4_party_switching.R</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_3_effect_of_winning_on_federal_congress.R</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_5_tab_7_rd_robust_estimations.R</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                      doi                                           file  \\\n0  doi:10.7910/DVN/XFQZI2                                 Condemnation.R   \n1  doi:10.7910/DVN/WGPDBS                       Replication_of_Figures.R   \n2  doi:10.7910/DVN/BPON3K              fig_10_effect_of_winning_on_gov.R   \n3  doi:10.7910/DVN/BPON3K                            fig_11_rd_placebo.R   \n4  doi:10.7910/DVN/BPON3K                      fig_12_historical_trend.R   \n5  doi:10.7910/DVN/BPON3K                   fig_13_plot_loyalty_df_pct.R   \n6  doi:10.7910/DVN/BPON3K          fig_14_effect_on_individual_parties.R   \n7  doi:10.7910/DVN/BPON3K                  fig_2_fig_4_party_switching.R   \n8  doi:10.7910/DVN/BPON3K  fig_3_effect_of_winning_on_federal_congress.R   \n9  doi:10.7910/DVN/BPON3K            fig_5_tab_7_rd_robust_estimations.R   \n\n                                                 r32      r36  \\\n0  Error in library(readstata13) : there is no pa...      NaN   \n1                                            success  success   \n2  Error in library(gridExtra) : there is no pack...      NaN   \n3  Error in library(gridExtra) : there is no pack...      NaN   \n4  Error in library(ggthemes) : there is no packa...      NaN   \n5  Error in library(gridExtra) : there is no pack...      NaN   \n6  Error in library(gridExtra) : there is no pack...      NaN   \n7  Error in library(gridExtra) : there is no pack...      NaN   \n8  Error in library(gridExtra) : there is no pack...      NaN   \n9  Error in library(gridExtra) : there is no pack...      NaN   \n\n                                                 r40   result  success  \n0                                                NaN      NaN      NaN  \n1                                            success  success      1.0  \n2  Error in library(gridExtra) : there is no pack...      NaN      NaN  \n3  Error in library(gridExtra) : there is no pack...      NaN      NaN  \n4  Error in library(ggthemes) : there is no packa...      NaN      NaN  \n5  Error in library(gridExtra) : there is no pack...      NaN      NaN  \n6  Error in library(gridExtra) : there is no pack...      NaN      NaN  \n7  Error in library(gridExtra) : there is no pack...      NaN      NaN  \n8  Error in library(gridExtra) : there is no pack...      NaN      NaN  \n9  Error in library(gridExtra) : there is no pack...      NaN      NaN  "
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "7985"
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exclude bad DOIs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "er_362 = pd.read_csv(\"data/run_log_r36_no_env_download.csv\", sep=\"\\t\", names=[\"doi\", \"fileid\", \"status\"])\n",
    "er_322 = pd.read_csv(\"data/run_log_r32_no_env_download.csv\", sep=\"\\t\", names=[\"doi\", \"fileid\", \"status\"])\n",
    "er_402 = pd.read_csv(\"data/run_log_r40_no_env_download.csv\", sep=\"\\t\", names=[\"doi\", \"fileid\", \"status\"])\n",
    "\n",
    "error_data = [er_322, er_362, er_402]\n",
    "\n",
    "exclude = []\n",
    "for er in error_data:\n",
    "    temp = er[er.status != 'ok']\n",
    "    bad_dois = temp['doi'].unique().tolist()\n",
    "    exclude.append(set(bad_dois))\n",
    "    \n",
    "bad_dois = exclude[0] & exclude[1] & exclude[2] \n",
    "bad_dois = list(bad_dois)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(df[df.doi.isin(bad_dois) & (df['result'] != 'success')].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>doi</th>\n      <th>file</th>\n      <th>r32</th>\n      <th>r36</th>\n      <th>r40</th>\n      <th>result</th>\n      <th>success</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>7980</th>\n      <td>doi:10.7910/DVN/NFXS5Z</td>\n      <td>psrm_supplementary_scriptX.R</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Error in library(stargazer) : there is no pack...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>7981</th>\n      <td>doi:10.7910/DVN/UMG39H</td>\n      <td>Figures.R</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Error: unexpected symbol in \\load(directory of\\\"\"</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>7982</th>\n      <td>doi:10.7910/DVN/UMG39H</td>\n      <td>Table1.R</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Error in read.dta('directory') :   unable to o...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>7983</th>\n      <td>doi:10.7910/DVN/UMG39H</td>\n      <td>Table2.R</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Error in readChar(con, 5L, useBytes = TRUE) : ...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>7984</th>\n      <td>doi:10.7910/DVN/T9WESH</td>\n      <td>unknown</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>download error</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                         doi                          file  r32  r36  \\\n7980  doi:10.7910/DVN/NFXS5Z  psrm_supplementary_scriptX.R  NaN  NaN   \n7981  doi:10.7910/DVN/UMG39H                     Figures.R  NaN  NaN   \n7982  doi:10.7910/DVN/UMG39H                      Table1.R  NaN  NaN   \n7983  doi:10.7910/DVN/UMG39H                      Table2.R  NaN  NaN   \n7984  doi:10.7910/DVN/T9WESH                       unknown  NaN  NaN   \n\n                                                    r40 result  success  \n7980  Error in library(stargazer) : there is no pack...    NaN      NaN  \n7981  Error: unexpected symbol in \\load(directory of\\\"\"    NaN      NaN  \n7982  Error in read.dta('directory') :   unable to o...    NaN      NaN  \n7983  Error in readChar(con, 5L, useBytes = TRUE) : ...    NaN      NaN  \n7984                                     download error    NaN      NaN  "
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "7659"
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "2071"
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.doi.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('data/aggregate_results_no_env.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quick check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "Total number of entries: 3830\nTotal number after bad DOIs are removed: 3830\nUnique DOIs: 1388\nSuccess: 952 out of 3830 => 0.2485639686684073\nTIL: 0 out of 3830 => 0.0\nError: 2878 out of 3830 => 0.7514360313315926\n"
    },
    {
     "data": {
      "image/png": "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\n",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Created with matplotlib (http://matplotlib.org/) -->\n<svg height=\"267.7275pt\" version=\"1.1\" viewBox=\"0 0 440.303125 267.7275\" width=\"440.303125pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <defs>\n  <style type=\"text/css\">\n*{stroke-linecap:butt;stroke-linejoin:round;}\n  </style>\n </defs>\n <g id=\"figure_1\">\n  <g id=\"patch_1\">\n   <path d=\"M 0 267.7275 \nL 440.303125 267.7275 \nL 440.303125 0 \nL 0 0 \nz\n\" style=\"fill:none;\"/>\n  </g>\n  <g id=\"axes_1\">\n   <g id=\"matplotlib.axis_1\"/>\n   <g id=\"matplotlib.axis_2\"/>\n   <g id=\"patch_2\">\n    <path d=\"M 299.273716 74.887131 \nC 292.672686 67.02033 284.944958 60.172262 276.34139 54.565231 \nC 267.737822 48.9582 258.35253 44.653541 248.490178 41.790992 \nC 238.627826 38.928444 228.396299 37.539318 218.127734 37.66871 \nC 207.859169 37.798102 197.665893 39.444596 187.878802 42.554743 \nC 178.09171 45.664891 168.817865 50.20467 160.358312 56.026709 \nC 151.89876 61.848749 144.34604 68.889362 137.94533 76.919996 \nC 131.54462 84.95063 126.365936 93.883437 122.577391 103.428441 \nC 118.788845 112.973445 116.43188 123.026231 115.583007 133.260468 \nC 114.734135 143.494704 115.402641 153.798436 117.566824 163.837186 \nC 119.731007 173.875935 123.367193 183.539886 128.357345 192.515328 \nC 133.347496 201.49077 139.637026 209.67952 147.021762 216.815755 \nC 154.406498 223.95199 162.805659 229.957645 171.946592 234.637766 \nC 181.087524 239.317887 190.870234 242.621277 200.977156 244.440701 \nC 211.084078 246.260126 221.404651 246.575682 231.603849 245.377126 \nC 241.803047 244.17857 251.7693 241.479014 261.179083 237.366089 \nC 270.588867 233.253165 279.339247 227.771864 287.146168 221.100121 \nL 219.440814 141.87489 \nL 299.273716 74.887131 \nz\n\" style=\"fill:#1f77b4;opacity:0.6;stroke:#ffffff;stroke-linejoin:miter;\"/>\n   </g>\n   <g id=\"patch_3\">\n    <path d=\"M 287.146168 221.100121 \nC 308.026355 203.256053 321.028251 177.861523 323.298621 150.489304 \nC 325.56899 123.117084 316.92865 95.927455 299.273704 74.887116 \nL 219.440814 141.87489 \nL 287.146168 221.100121 \nz\n\" style=\"fill:#ff7f0e;opacity:0.6;stroke:#ffffff;stroke-linejoin:miter;\"/>\n   </g>\n   <g id=\"patch_4\">\n    <path clip-path=\"url(#p9772d2f126)\" d=\"M 219.440814 214.825008 \nC 238.787411 214.825008 257.344226 207.138523 271.024336 193.458413 \nC 284.704446 179.778303 292.390931 161.221488 292.390931 141.87489 \nC 292.390931 122.528293 284.704446 103.971478 271.024336 90.291368 \nC 257.344226 76.611258 238.787411 68.924773 219.440814 68.924773 \nC 200.094216 68.924773 181.537401 76.611258 167.857291 90.291368 \nC 154.177181 103.971478 146.490697 122.528293 146.490697 141.87489 \nC 146.490697 161.221488 154.177181 179.778303 167.857291 193.458413 \nC 181.537401 207.138523 200.094216 214.825008 219.440814 214.825008 \nz\n\" style=\"fill:#ffffff;stroke:#ffffff;stroke-linejoin:miter;\"/>\n   </g>\n   <g id=\"text_1\">\n    <!-- Error -->\n    <defs>\n     <path d=\"M 20.90625 62.59375 \nL 20.90625 36.421875 \nL 35.453125 36.421875 \nQ 41.109375 36.421875 43.015625 38.140625 \nQ 45.5625 40.375 45.84375 46.046875 \nL 47.65625 46.046875 \nL 47.65625 23 \nL 45.84375 23 \nQ 45.171875 27.828125 44.484375 29.203125 \nQ 43.609375 30.90625 41.59375 31.875 \nQ 39.59375 32.859375 35.453125 32.859375 \nL 20.90625 32.859375 \nL 20.90625 11.03125 \nQ 20.90625 6.640625 21.296875 5.6875 \nQ 21.6875 4.734375 22.65625 4.171875 \nQ 23.640625 3.609375 26.375 3.609375 \nL 37.59375 3.609375 \nQ 43.21875 3.609375 45.75 4.390625 \nQ 48.296875 5.171875 50.640625 7.46875 \nQ 53.65625 10.5 56.84375 16.609375 \nL 58.796875 16.609375 \nL 53.078125 0 \nL 2.046875 0 \nL 2.046875 1.8125 \nL 4.390625 1.8125 \nQ 6.734375 1.8125 8.84375 2.9375 \nQ 10.40625 3.71875 10.96875 5.28125 \nQ 11.53125 6.84375 11.53125 11.671875 \nL 11.53125 54.6875 \nQ 11.53125 60.984375 10.25 62.453125 \nQ 8.5 64.40625 4.390625 64.40625 \nL 2.046875 64.40625 \nL 2.046875 66.21875 \nL 53.078125 66.21875 \nL 53.8125 51.703125 \nL 51.90625 51.703125 \nQ 50.875 56.9375 49.625 58.890625 \nQ 48.390625 60.84375 45.953125 61.859375 \nQ 44 62.59375 39.0625 62.59375 \nz\n\" id=\"TimesNewRomanPSMT-45\"/>\n     <path d=\"M 16.21875 46.046875 \nL 16.21875 35.984375 \nQ 21.828125 46.046875 27.734375 46.046875 \nQ 30.421875 46.046875 32.171875 44.40625 \nQ 33.9375 42.78125 33.9375 40.625 \nQ 33.9375 38.71875 32.65625 37.390625 \nQ 31.390625 36.078125 29.640625 36.078125 \nQ 27.9375 36.078125 25.8125 37.765625 \nQ 23.6875 39.453125 22.65625 39.453125 \nQ 21.78125 39.453125 20.75 38.484375 \nQ 18.5625 36.46875 16.21875 31.890625 \nL 16.21875 10.453125 \nQ 16.21875 6.734375 17.140625 4.828125 \nQ 17.78125 3.515625 19.390625 2.640625 \nQ 21 1.765625 24.03125 1.765625 \nL 24.03125 0 \nL 1.125 0 \nL 1.125 1.765625 \nQ 4.546875 1.765625 6.203125 2.828125 \nQ 7.421875 3.609375 7.90625 5.328125 \nQ 8.15625 6.15625 8.15625 10.0625 \nL 8.15625 27.390625 \nQ 8.15625 35.203125 7.828125 36.6875 \nQ 7.515625 38.1875 6.65625 38.859375 \nQ 5.8125 39.546875 4.546875 39.546875 \nQ 3.03125 39.546875 1.125 38.8125 \nL 0.640625 40.578125 \nL 14.15625 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-72\"/>\n     <path d=\"M 25 46.046875 \nQ 35.15625 46.046875 41.3125 38.328125 \nQ 46.53125 31.734375 46.53125 23.1875 \nQ 46.53125 17.1875 43.640625 11.03125 \nQ 40.765625 4.890625 35.71875 1.75 \nQ 30.671875 -1.375 24.46875 -1.375 \nQ 14.359375 -1.375 8.40625 6.6875 \nQ 3.375 13.484375 3.375 21.921875 \nQ 3.375 28.078125 6.421875 34.15625 \nQ 9.46875 40.234375 14.453125 43.140625 \nQ 19.4375 46.046875 25 46.046875 \nz\nM 23.484375 42.875 \nQ 20.90625 42.875 18.28125 41.328125 \nQ 15.671875 39.796875 14.0625 35.9375 \nQ 12.453125 32.078125 12.453125 26.03125 \nQ 12.453125 16.265625 16.328125 9.171875 \nQ 20.21875 2.09375 26.5625 2.09375 \nQ 31.296875 2.09375 34.375 6 \nQ 37.453125 9.90625 37.453125 19.4375 \nQ 37.453125 31.34375 32.328125 38.1875 \nQ 28.859375 42.875 23.484375 42.875 \nz\n\" id=\"TimesNewRomanPSMT-6f\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(71.442227 136.242775)scale(0.16 -0.16)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-45\"/>\n     <use x=\"61.083984\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"94.384766\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"127.685547\" xlink:href=\"#TimesNewRomanPSMT-6f\"/>\n     <use x=\"177.685547\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n    </g>\n   </g>\n   <g id=\"text_2\">\n    <!-- 75.14%  (2878) -->\n    <defs>\n     <path d=\"M 10.0625 66.21875 \nL 45.5625 66.21875 \nL 45.5625 64.359375 \nL 23.484375 -1.375 \nL 18.015625 -1.375 \nL 37.796875 58.25 \nL 19.578125 58.25 \nQ 14.0625 58.25 11.71875 56.9375 \nQ 7.625 54.6875 5.125 50 \nL 3.71875 50.53125 \nz\n\" id=\"TimesNewRomanPSMT-37\"/>\n     <path d=\"M 43.40625 66.21875 \nL 39.59375 57.90625 \nL 19.671875 57.90625 \nL 15.328125 49.03125 \nQ 28.265625 47.125 35.84375 39.40625 \nQ 42.328125 32.765625 42.328125 23.78125 \nQ 42.328125 18.5625 40.203125 14.109375 \nQ 38.09375 9.671875 34.859375 6.546875 \nQ 31.640625 3.421875 27.6875 1.515625 \nQ 22.078125 -1.171875 16.15625 -1.171875 \nQ 10.203125 -1.171875 7.484375 0.84375 \nQ 4.78125 2.875 4.78125 5.328125 \nQ 4.78125 6.6875 5.90625 7.734375 \nQ 7.03125 8.796875 8.734375 8.796875 \nQ 10.015625 8.796875 10.96875 8.40625 \nQ 11.921875 8.015625 14.203125 6.390625 \nQ 17.875 3.859375 21.625 3.859375 \nQ 27.34375 3.859375 31.65625 8.171875 \nQ 35.984375 12.5 35.984375 18.703125 \nQ 35.984375 24.703125 32.125 29.90625 \nQ 28.265625 35.109375 21.484375 37.9375 \nQ 16.15625 40.140625 6.984375 40.484375 \nL 19.671875 66.21875 \nz\n\" id=\"TimesNewRomanPSMT-35\"/>\n     <path d=\"M 12.5 9.46875 \nQ 14.796875 9.46875 16.359375 7.875 \nQ 17.921875 6.296875 17.921875 4.046875 \nQ 17.921875 1.8125 16.328125 0.21875 \nQ 14.75 -1.375 12.5 -1.375 \nQ 10.25 -1.375 8.65625 0.21875 \nQ 7.078125 1.8125 7.078125 4.046875 \nQ 7.078125 6.34375 8.65625 7.90625 \nQ 10.25 9.46875 12.5 9.46875 \nz\n\" id=\"TimesNewRomanPSMT-2e\"/>\n     <path d=\"M 11.71875 59.71875 \nL 27.828125 67.578125 \nL 29.4375 67.578125 \nL 29.4375 11.671875 \nQ 29.4375 6.109375 29.90625 4.734375 \nQ 30.375 3.375 31.828125 2.640625 \nQ 33.296875 1.90625 37.796875 1.8125 \nL 37.796875 0 \nL 12.890625 0 \nL 12.890625 1.8125 \nQ 17.578125 1.90625 18.9375 2.609375 \nQ 20.3125 3.328125 20.84375 4.515625 \nQ 21.390625 5.71875 21.390625 11.671875 \nL 21.390625 47.40625 \nQ 21.390625 54.640625 20.90625 56.6875 \nQ 20.5625 58.25 19.65625 58.984375 \nQ 18.75 59.71875 17.484375 59.71875 \nQ 15.671875 59.71875 12.453125 58.203125 \nz\n\" id=\"TimesNewRomanPSMT-31\"/>\n     <path d=\"M 46.53125 24.421875 \nL 46.53125 17.484375 \nL 37.640625 17.484375 \nL 37.640625 0 \nL 29.59375 0 \nL 29.59375 17.484375 \nL 1.5625 17.484375 \nL 1.5625 23.734375 \nL 32.28125 67.578125 \nL 37.640625 67.578125 \nL 37.640625 24.421875 \nz\nM 29.59375 24.421875 \nL 29.59375 57.28125 \nL 6.34375 24.421875 \nz\n\" id=\"TimesNewRomanPSMT-34\"/>\n     <path d=\"M 67.96875 67.71875 \nL 19.734375 -2.734375 \nL 15.375 -2.734375 \nL 63.625 67.71875 \nz\nM 17.78125 67.71875 \nQ 24.359375 67.71875 28 62.25 \nQ 31.640625 56.78125 31.640625 49.703125 \nQ 31.640625 41.21875 27.53125 36.578125 \nQ 23.4375 31.9375 17.671875 31.9375 \nQ 13.8125 31.9375 10.59375 34.0625 \nQ 7.375 36.1875 5.4375 40.375 \nQ 3.515625 44.578125 3.515625 49.703125 \nQ 3.515625 54.828125 5.46875 59.15625 \nQ 7.421875 63.484375 10.8125 65.59375 \nQ 14.203125 67.71875 17.78125 67.71875 \nz\nM 17.625 64.984375 \nQ 15.140625 64.984375 13.203125 62.046875 \nQ 11.28125 59.125 11.28125 49.75 \nQ 11.28125 42.96875 12.359375 39.40625 \nQ 13.1875 36.71875 14.9375 35.25 \nQ 15.96875 34.375 17.484375 34.375 \nQ 19.828125 34.375 21.484375 36.921875 \nQ 23.921875 40.671875 23.921875 49.46875 \nQ 23.921875 58.734375 21.53125 62.5 \nQ 19.96875 64.984375 17.625 64.984375 \nz\nM 65.71875 32.859375 \nQ 69.1875 32.859375 72.625 30.65625 \nQ 76.078125 28.46875 77.953125 24.265625 \nQ 79.828125 20.0625 79.828125 15.046875 \nQ 79.828125 6.390625 75.671875 1.828125 \nQ 71.53125 -2.734375 65.875 -2.734375 \nQ 62.3125 -2.734375 58.953125 -0.53125 \nQ 55.609375 1.65625 53.6875 5.734375 \nQ 51.765625 9.8125 51.765625 15.046875 \nQ 51.765625 20.171875 53.6875 24.40625 \nQ 55.609375 28.65625 58.953125 30.75 \nQ 62.3125 32.859375 65.71875 32.859375 \nz\nM 65.765625 30.28125 \nQ 63.421875 30.28125 61.71875 27.640625 \nQ 59.515625 24.21875 59.515625 14.703125 \nQ 59.515625 5.953125 61.765625 2.484375 \nQ 63.421875 0 65.765625 0 \nQ 68.015625 0 69.78125 2.6875 \nQ 72.125 6.25 72.125 14.9375 \nQ 72.125 24.125 69.78125 27.78125 \nQ 68.171875 30.28125 65.765625 30.28125 \nz\n\" id=\"TimesNewRomanPSMT-25\"/>\n     <path id=\"TimesNewRomanPSMT-20\"/>\n     <path d=\"M 31.0625 -19.578125 \nL 31.0625 -21.390625 \nQ 23.6875 -17.671875 18.75 -12.703125 \nQ 11.71875 -5.609375 7.90625 4 \nQ 4.109375 13.625 4.109375 23.96875 \nQ 4.109375 39.109375 11.578125 51.578125 \nQ 19.046875 64.0625 31.0625 69.4375 \nL 31.0625 67.390625 \nQ 25.046875 64.0625 21.1875 58.296875 \nQ 17.328125 52.546875 15.421875 43.703125 \nQ 13.53125 34.859375 13.53125 25.25 \nQ 13.53125 14.796875 15.140625 6.25 \nQ 16.40625 -0.484375 18.203125 -4.5625 \nQ 20.015625 -8.640625 23.0625 -12.390625 \nQ 26.125 -16.15625 31.0625 -19.578125 \nz\n\" id=\"TimesNewRomanPSMT-28\"/>\n     <path d=\"M 45.84375 12.75 \nL 41.21875 0 \nL 2.15625 0 \nL 2.15625 1.8125 \nQ 19.390625 17.53125 26.421875 27.484375 \nQ 33.453125 37.453125 33.453125 45.703125 \nQ 33.453125 52 29.59375 56.046875 \nQ 25.734375 60.109375 20.359375 60.109375 \nQ 15.484375 60.109375 11.59375 57.25 \nQ 7.71875 54.390625 5.859375 48.875 \nL 4.046875 48.875 \nQ 5.28125 57.90625 10.328125 62.734375 \nQ 15.375 67.578125 22.953125 67.578125 \nQ 31 67.578125 36.390625 62.40625 \nQ 41.796875 57.234375 41.796875 50.203125 \nQ 41.796875 45.171875 39.453125 40.140625 \nQ 35.84375 32.234375 27.734375 23.390625 \nQ 15.578125 10.109375 12.546875 7.375 \nL 29.828125 7.375 \nQ 35.109375 7.375 37.234375 7.765625 \nQ 39.359375 8.15625 41.0625 9.34375 \nQ 42.78125 10.546875 44.046875 12.75 \nz\n\" id=\"TimesNewRomanPSMT-32\"/>\n     <path d=\"M 19.1875 33.34375 \nQ 11.328125 39.796875 9.046875 43.703125 \nQ 6.78125 47.609375 6.78125 51.8125 \nQ 6.78125 58.25 11.765625 62.90625 \nQ 16.75 67.578125 25 67.578125 \nQ 33.015625 67.578125 37.890625 63.234375 \nQ 42.78125 58.890625 42.78125 53.328125 \nQ 42.78125 49.609375 40.140625 45.75 \nQ 37.5 41.890625 29.15625 36.671875 \nQ 37.75 30.03125 40.53125 26.21875 \nQ 44.234375 21.234375 44.234375 15.71875 \nQ 44.234375 8.734375 38.90625 3.78125 \nQ 33.59375 -1.171875 24.953125 -1.171875 \nQ 15.53125 -1.171875 10.25 4.734375 \nQ 6.0625 9.46875 6.0625 15.09375 \nQ 6.0625 19.484375 9.015625 23.796875 \nQ 11.96875 28.125 19.1875 33.34375 \nz\nM 26.859375 38.578125 \nQ 32.71875 43.84375 34.28125 46.890625 \nQ 35.84375 49.953125 35.84375 53.8125 \nQ 35.84375 58.9375 32.953125 61.84375 \nQ 30.078125 64.75 25.09375 64.75 \nQ 20.125 64.75 17 61.859375 \nQ 13.875 58.984375 13.875 55.125 \nQ 13.875 52.59375 15.15625 50.046875 \nQ 16.453125 47.515625 18.84375 45.21875 \nz\nM 21.484375 31.5 \nQ 17.4375 28.078125 15.484375 24.046875 \nQ 13.53125 20.015625 13.53125 15.328125 \nQ 13.53125 9.03125 16.96875 5.25 \nQ 20.40625 1.46875 25.734375 1.46875 \nQ 31 1.46875 34.171875 4.4375 \nQ 37.359375 7.421875 37.359375 11.671875 \nQ 37.359375 15.1875 35.5 17.96875 \nQ 32.03125 23.140625 21.484375 31.5 \nz\n\" id=\"TimesNewRomanPSMT-38\"/>\n     <path d=\"M 2.25 67.390625 \nL 2.25 69.4375 \nQ 9.671875 65.765625 14.59375 60.796875 \nQ 21.578125 53.65625 25.390625 44.0625 \nQ 29.203125 34.46875 29.203125 24.078125 \nQ 29.203125 8.9375 21.75 -3.53125 \nQ 14.3125 -16.015625 2.25 -21.390625 \nL 2.25 -19.578125 \nQ 8.25 -16.21875 12.125 -10.46875 \nQ 16.015625 -4.734375 17.890625 4.125 \nQ 19.78125 12.984375 19.78125 22.609375 \nQ 19.78125 33.015625 18.171875 41.609375 \nQ 16.9375 48.34375 15.109375 52.390625 \nQ 13.28125 56.453125 10.25 60.203125 \nQ 7.234375 63.96875 2.25 67.390625 \nz\n\" id=\"TimesNewRomanPSMT-29\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(113.383786 140.069518)scale(0.14 -0.14)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-37\"/>\n     <use x=\"50\" xlink:href=\"#TimesNewRomanPSMT-35\"/>\n     <use x=\"100\" xlink:href=\"#TimesNewRomanPSMT-2e\"/>\n     <use x=\"125\" xlink:href=\"#TimesNewRomanPSMT-31\"/>\n     <use x=\"175\" xlink:href=\"#TimesNewRomanPSMT-34\"/>\n     <use x=\"225\" xlink:href=\"#TimesNewRomanPSMT-25\"/>\n     <use x=\"308.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"333.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"358.300781\" xlink:href=\"#TimesNewRomanPSMT-28\"/>\n     <use x=\"391.601562\" xlink:href=\"#TimesNewRomanPSMT-32\"/>\n     <use x=\"441.601562\" xlink:href=\"#TimesNewRomanPSMT-38\"/>\n     <use x=\"491.601562\" xlink:href=\"#TimesNewRomanPSMT-37\"/>\n     <use x=\"541.601562\" xlink:href=\"#TimesNewRomanPSMT-38\"/>\n     <use x=\"591.601562\" xlink:href=\"#TimesNewRomanPSMT-29\"/>\n    </g>\n   </g>\n   <g id=\"text_3\">\n    <!-- Success -->\n    <defs>\n     <path d=\"M 45.84375 67.71875 \nL 45.84375 44.828125 \nL 44.046875 44.828125 \nQ 43.171875 51.421875 40.890625 55.328125 \nQ 38.625 59.234375 34.421875 61.515625 \nQ 30.21875 63.8125 25.734375 63.8125 \nQ 20.65625 63.8125 17.328125 60.71875 \nQ 14.015625 57.625 14.015625 53.65625 \nQ 14.015625 50.640625 16.109375 48.140625 \nQ 19.140625 44.484375 30.515625 38.375 \nQ 39.796875 33.40625 43.1875 30.734375 \nQ 46.578125 28.078125 48.40625 24.453125 \nQ 50.25 20.84375 50.25 16.890625 \nQ 50.25 9.375 44.40625 3.921875 \nQ 38.578125 -1.515625 29.390625 -1.515625 \nQ 26.515625 -1.515625 23.96875 -1.078125 \nQ 22.46875 -0.828125 17.703125 0.703125 \nQ 12.9375 2.25 11.671875 2.25 \nQ 10.453125 2.25 9.734375 1.515625 \nQ 9.03125 0.78125 8.6875 -1.515625 \nL 6.890625 -1.515625 \nL 6.890625 21.1875 \nL 8.6875 21.1875 \nQ 9.96875 14.0625 12.109375 10.515625 \nQ 14.265625 6.984375 18.671875 4.640625 \nQ 23.09375 2.296875 28.375 2.296875 \nQ 34.46875 2.296875 38 5.515625 \nQ 41.546875 8.734375 41.546875 13.140625 \nQ 41.546875 15.578125 40.203125 18.0625 \nQ 38.875 20.5625 36.03125 22.703125 \nQ 34.125 24.171875 25.625 28.921875 \nQ 17.140625 33.6875 13.546875 36.515625 \nQ 9.96875 39.359375 8.109375 42.765625 \nQ 6.25 46.1875 6.25 50.296875 \nQ 6.25 57.421875 11.71875 62.5625 \nQ 17.1875 67.71875 25.640625 67.71875 \nQ 30.90625 67.71875 36.8125 65.140625 \nQ 39.546875 63.921875 40.671875 63.921875 \nQ 41.9375 63.921875 42.75 64.671875 \nQ 43.5625 65.4375 44.046875 67.71875 \nz\n\" id=\"TimesNewRomanPSMT-53\"/>\n     <path d=\"M 42.328125 44.734375 \nL 42.328125 17.625 \nQ 42.328125 9.859375 42.6875 8.125 \nQ 43.0625 6.390625 43.859375 5.703125 \nQ 44.671875 5.03125 45.75 5.03125 \nQ 47.265625 5.03125 49.171875 5.859375 \nL 49.859375 4.15625 \nL 36.46875 -1.375 \nL 34.28125 -1.375 \nL 34.28125 8.109375 \nQ 28.515625 1.859375 25.484375 0.234375 \nQ 22.46875 -1.375 19.09375 -1.375 \nQ 15.328125 -1.375 12.5625 0.796875 \nQ 9.8125 2.984375 8.734375 6.390625 \nQ 7.671875 9.8125 7.671875 16.0625 \nL 7.671875 36.03125 \nQ 7.671875 39.203125 6.984375 40.421875 \nQ 6.296875 41.65625 4.953125 42.3125 \nQ 3.609375 42.96875 0.09375 42.921875 \nL 0.09375 44.734375 \nL 15.765625 44.734375 \nL 15.765625 14.796875 \nQ 15.765625 8.546875 17.9375 6.59375 \nQ 20.125 4.640625 23.1875 4.640625 \nQ 25.296875 4.640625 27.953125 5.953125 \nQ 30.609375 7.28125 34.28125 10.984375 \nL 34.28125 36.328125 \nQ 34.28125 40.140625 32.890625 41.484375 \nQ 31.5 42.828125 27.09375 42.921875 \nL 27.09375 44.734375 \nz\n\" id=\"TimesNewRomanPSMT-75\"/>\n     <path d=\"M 41.109375 17 \nQ 39.3125 8.15625 34.03125 3.390625 \nQ 28.765625 -1.375 22.359375 -1.375 \nQ 14.75 -1.375 9.078125 5.015625 \nQ 3.421875 11.421875 3.421875 22.3125 \nQ 3.421875 32.859375 9.6875 39.453125 \nQ 15.96875 46.046875 24.75 46.046875 \nQ 31.34375 46.046875 35.59375 42.546875 \nQ 39.84375 39.0625 39.84375 35.296875 \nQ 39.84375 33.453125 38.640625 32.296875 \nQ 37.453125 31.15625 35.296875 31.15625 \nQ 32.421875 31.15625 30.953125 33.015625 \nQ 30.125 34.03125 29.859375 36.90625 \nQ 29.59375 39.796875 27.875 41.3125 \nQ 26.171875 42.78125 23.140625 42.78125 \nQ 18.265625 42.78125 15.28125 39.15625 \nQ 11.328125 34.375 11.328125 26.515625 \nQ 11.328125 18.5 15.25 12.375 \nQ 19.1875 6.25 25.875 6.25 \nQ 30.671875 6.25 34.46875 9.515625 \nQ 37.15625 11.765625 39.703125 17.671875 \nz\n\" id=\"TimesNewRomanPSMT-63\"/>\n     <path d=\"M 10.640625 27.875 \nQ 10.59375 17.921875 15.484375 12.25 \nQ 20.359375 6.59375 26.953125 6.59375 \nQ 31.34375 6.59375 34.59375 9 \nQ 37.84375 11.421875 40.046875 17.28125 \nL 41.546875 16.3125 \nQ 40.53125 9.625 35.59375 4.125 \nQ 30.671875 -1.375 23.25 -1.375 \nQ 15.1875 -1.375 9.453125 4.90625 \nQ 3.71875 11.1875 3.71875 21.78125 \nQ 3.71875 33.25 9.59375 39.671875 \nQ 15.484375 46.09375 24.359375 46.09375 \nQ 31.890625 46.09375 36.71875 41.140625 \nQ 41.546875 36.1875 41.546875 27.875 \nz\nM 10.640625 30.71875 \nL 31.34375 30.71875 \nQ 31.109375 35.015625 30.328125 36.765625 \nQ 29.109375 39.5 26.6875 41.0625 \nQ 24.265625 42.625 21.625 42.625 \nQ 17.578125 42.625 14.375 39.46875 \nQ 11.1875 36.328125 10.640625 30.71875 \nz\n\" id=\"TimesNewRomanPSMT-65\"/>\n     <path d=\"M 32.03125 46.046875 \nL 32.03125 30.8125 \nL 30.421875 30.8125 \nQ 28.5625 37.984375 25.65625 40.578125 \nQ 22.75 43.171875 18.265625 43.171875 \nQ 14.84375 43.171875 12.734375 41.359375 \nQ 10.640625 39.546875 10.640625 37.359375 \nQ 10.640625 34.625 12.203125 32.671875 \nQ 13.71875 30.671875 18.359375 28.421875 \nL 25.484375 24.953125 \nQ 35.40625 20.125 35.40625 12.203125 \nQ 35.40625 6.109375 30.78125 2.359375 \nQ 26.171875 -1.375 20.453125 -1.375 \nQ 16.359375 -1.375 11.078125 0.09375 \nQ 9.46875 0.59375 8.453125 0.59375 \nQ 7.328125 0.59375 6.6875 -0.6875 \nL 5.078125 -0.6875 \nL 5.078125 15.28125 \nL 6.6875 15.28125 \nQ 8.0625 8.453125 11.90625 4.984375 \nQ 15.765625 1.515625 20.5625 1.515625 \nQ 23.921875 1.515625 26.046875 3.484375 \nQ 28.171875 5.46875 28.171875 8.25 \nQ 28.171875 11.625 25.796875 13.921875 \nQ 23.4375 16.21875 16.359375 19.734375 \nQ 9.28125 23.25 7.078125 26.078125 \nQ 4.890625 28.859375 4.890625 33.109375 \nQ 4.890625 38.625 8.671875 42.328125 \nQ 12.453125 46.046875 18.453125 46.046875 \nQ 21.09375 46.046875 24.859375 44.921875 \nQ 27.34375 44.1875 28.171875 44.1875 \nQ 28.953125 44.1875 29.390625 44.53125 \nQ 29.828125 44.875 30.421875 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-73\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(333.684401 155.194495)scale(0.16 -0.16)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-53\"/>\n     <use x=\"55.615234\" xlink:href=\"#TimesNewRomanPSMT-75\"/>\n     <use x=\"105.615234\" xlink:href=\"#TimesNewRomanPSMT-63\"/>\n     <use x=\"150\" xlink:href=\"#TimesNewRomanPSMT-63\"/>\n     <use x=\"194.384766\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"238.769531\" xlink:href=\"#TimesNewRomanPSMT-73\"/>\n     <use x=\"277.685547\" xlink:href=\"#TimesNewRomanPSMT-73\"/>\n    </g>\n   </g>\n   <g id=\"text_4\">\n    <!-- 24.86%  (952) -->\n    <defs>\n     <path d=\"M 44.828125 67.578125 \nL 44.828125 65.765625 \nQ 38.375 65.140625 34.296875 63.203125 \nQ 30.21875 61.28125 26.234375 57.328125 \nQ 22.265625 53.375 19.65625 48.515625 \nQ 17.046875 43.65625 15.28125 36.96875 \nQ 22.3125 41.796875 29.390625 41.796875 \nQ 36.1875 41.796875 41.15625 36.328125 \nQ 46.140625 30.859375 46.140625 22.265625 \nQ 46.140625 13.96875 41.109375 7.125 \nQ 35.0625 -1.171875 25.09375 -1.171875 \nQ 18.3125 -1.171875 13.578125 3.328125 \nQ 4.296875 12.0625 4.296875 25.984375 \nQ 4.296875 34.859375 7.859375 42.859375 \nQ 11.421875 50.875 18.03125 57.078125 \nQ 24.65625 63.28125 30.703125 65.421875 \nQ 36.765625 67.578125 42 67.578125 \nz\nM 14.453125 33.40625 \nQ 13.578125 26.8125 13.578125 22.75 \nQ 13.578125 18.0625 15.3125 12.5625 \nQ 17.046875 7.078125 20.453125 3.859375 \nQ 22.953125 1.5625 26.515625 1.5625 \nQ 30.765625 1.5625 34.109375 5.5625 \nQ 37.453125 9.578125 37.453125 17 \nQ 37.453125 25.34375 34.125 31.4375 \nQ 30.8125 37.546875 24.703125 37.546875 \nQ 22.859375 37.546875 20.734375 36.765625 \nQ 18.609375 35.984375 14.453125 33.40625 \nz\n\" id=\"TimesNewRomanPSMT-36\"/>\n     <path d=\"M 5.28125 -1.375 \nL 5.28125 0.4375 \nQ 11.625 0.53125 17.09375 3.390625 \nQ 22.5625 6.25 27.65625 13.375 \nQ 32.765625 20.515625 34.765625 29.046875 \nQ 27.09375 24.125 20.90625 24.125 \nQ 13.921875 24.125 8.9375 29.515625 \nQ 3.953125 34.90625 3.953125 43.84375 \nQ 3.953125 52.546875 8.9375 59.328125 \nQ 14.9375 67.578125 24.609375 67.578125 \nQ 32.765625 67.578125 38.578125 60.84375 \nQ 45.703125 52.484375 45.703125 40.234375 \nQ 45.703125 29.203125 40.28125 19.65625 \nQ 34.859375 10.109375 25.203125 3.8125 \nQ 17.328125 -1.375 8.0625 -1.375 \nz\nM 35.546875 32.671875 \nQ 36.421875 39.015625 36.421875 42.828125 \nQ 36.421875 47.5625 34.8125 53.046875 \nQ 33.203125 58.546875 30.25 61.46875 \nQ 27.296875 64.40625 23.53125 64.40625 \nQ 19.1875 64.40625 15.90625 60.5 \nQ 12.640625 56.59375 12.640625 48.875 \nQ 12.640625 38.578125 17 32.765625 \nQ 20.171875 28.5625 24.8125 28.5625 \nQ 27.046875 28.5625 30.125 29.640625 \nQ 33.203125 30.71875 35.546875 32.671875 \nz\n\" id=\"TimesNewRomanPSMT-39\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(241.513154 150.40682)scale(0.14 -0.14)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-32\"/>\n     <use x=\"50\" xlink:href=\"#TimesNewRomanPSMT-34\"/>\n     <use x=\"100\" xlink:href=\"#TimesNewRomanPSMT-2e\"/>\n     <use x=\"125\" xlink:href=\"#TimesNewRomanPSMT-38\"/>\n     <use x=\"175\" xlink:href=\"#TimesNewRomanPSMT-36\"/>\n     <use x=\"225\" xlink:href=\"#TimesNewRomanPSMT-25\"/>\n     <use x=\"308.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"333.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"358.300781\" xlink:href=\"#TimesNewRomanPSMT-28\"/>\n     <use x=\"391.601562\" xlink:href=\"#TimesNewRomanPSMT-39\"/>\n     <use x=\"441.601562\" xlink:href=\"#TimesNewRomanPSMT-35\"/>\n     <use x=\"491.601562\" xlink:href=\"#TimesNewRomanPSMT-32\"/>\n     <use x=\"541.601562\" xlink:href=\"#TimesNewRomanPSMT-29\"/>\n    </g>\n   </g>\n   <g id=\"text_5\">\n    <!-- Total re-execution rate per file without code cleaning -->\n    <defs>\n     <path d=\"M 57.859375 66.21875 \nL 58.59375 50.6875 \nL 56.734375 50.6875 \nQ 56.203125 54.78125 55.28125 56.546875 \nQ 53.765625 59.375 51.25 60.71875 \nQ 48.734375 62.0625 44.625 62.0625 \nL 35.296875 62.0625 \nL 35.296875 11.46875 \nQ 35.296875 5.375 36.625 3.859375 \nQ 38.484375 1.8125 42.328125 1.8125 \nL 44.625 1.8125 \nL 44.625 0 \nL 16.546875 0 \nL 16.546875 1.8125 \nL 18.890625 1.8125 \nQ 23.09375 1.8125 24.859375 4.34375 \nQ 25.921875 5.90625 25.921875 11.46875 \nL 25.921875 62.0625 \nL 17.96875 62.0625 \nQ 13.328125 62.0625 11.375 61.375 \nQ 8.84375 60.453125 7.03125 57.8125 \nQ 5.21875 55.171875 4.890625 50.6875 \nL 3.03125 50.6875 \nL 3.8125 66.21875 \nz\n\" id=\"TimesNewRomanPSMT-54\"/>\n     <path d=\"M 16.109375 59.421875 \nL 16.109375 44.734375 \nL 26.5625 44.734375 \nL 26.5625 41.3125 \nL 16.109375 41.3125 \nL 16.109375 12.3125 \nQ 16.109375 7.953125 17.359375 6.4375 \nQ 18.609375 4.9375 20.5625 4.9375 \nQ 22.171875 4.9375 23.6875 5.9375 \nQ 25.203125 6.9375 26.03125 8.890625 \nL 27.9375 8.890625 \nQ 26.21875 4.109375 23.09375 1.6875 \nQ 19.96875 -0.734375 16.65625 -0.734375 \nQ 14.40625 -0.734375 12.25 0.515625 \nQ 10.109375 1.765625 9.078125 4.078125 \nQ 8.0625 6.390625 8.0625 11.234375 \nL 8.0625 41.3125 \nL 0.984375 41.3125 \nL 0.984375 42.921875 \nQ 3.65625 44 6.46875 46.5625 \nQ 9.28125 49.125 11.46875 52.640625 \nQ 12.59375 54.5 14.59375 59.421875 \nz\n\" id=\"TimesNewRomanPSMT-74\"/>\n     <path d=\"M 28.46875 6.453125 \nQ 21.578125 1.125 19.828125 0.296875 \nQ 17.1875 -0.921875 14.203125 -0.921875 \nQ 9.578125 -0.921875 6.5625 2.25 \nQ 3.5625 5.421875 3.5625 10.59375 \nQ 3.5625 13.875 5.03125 16.265625 \nQ 7.03125 19.578125 11.984375 22.5 \nQ 16.9375 25.4375 28.46875 29.640625 \nL 28.46875 31.390625 \nQ 28.46875 38.09375 26.34375 40.578125 \nQ 24.21875 43.0625 20.171875 43.0625 \nQ 17.09375 43.0625 15.28125 41.40625 \nQ 13.421875 39.75 13.421875 37.59375 \nL 13.53125 34.765625 \nQ 13.53125 32.515625 12.375 31.296875 \nQ 11.234375 30.078125 9.375 30.078125 \nQ 7.5625 30.078125 6.421875 31.34375 \nQ 5.28125 32.625 5.28125 34.8125 \nQ 5.28125 39.015625 9.578125 42.53125 \nQ 13.875 46.046875 21.625 46.046875 \nQ 27.59375 46.046875 31.390625 44.046875 \nQ 34.28125 42.53125 35.640625 39.3125 \nQ 36.53125 37.203125 36.53125 30.71875 \nL 36.53125 15.53125 \nQ 36.53125 9.125 36.765625 7.6875 \nQ 37.015625 6.25 37.578125 5.765625 \nQ 38.140625 5.28125 38.875 5.28125 \nQ 39.65625 5.28125 40.234375 5.609375 \nQ 41.265625 6.25 44.1875 9.1875 \nL 44.1875 6.453125 \nQ 38.71875 -0.875 33.734375 -0.875 \nQ 31.34375 -0.875 29.921875 0.78125 \nQ 28.515625 2.4375 28.46875 6.453125 \nz\nM 28.46875 9.625 \nL 28.46875 26.65625 \nQ 21.09375 23.734375 18.953125 22.515625 \nQ 15.09375 20.359375 13.421875 18.015625 \nQ 11.765625 15.671875 11.765625 12.890625 \nQ 11.765625 9.375 13.859375 7.046875 \nQ 15.96875 4.734375 18.703125 4.734375 \nQ 22.40625 4.734375 28.46875 9.625 \nz\n\" id=\"TimesNewRomanPSMT-61\"/>\n     <path d=\"M 18.5 69.4375 \nL 18.5 10.109375 \nQ 18.5 5.90625 19.109375 4.53125 \nQ 19.734375 3.171875 21 2.46875 \nQ 22.265625 1.765625 25.734375 1.765625 \nL 25.734375 0 \nL 3.8125 0 \nL 3.8125 1.765625 \nQ 6.890625 1.765625 8 2.390625 \nQ 9.125 3.03125 9.765625 4.484375 \nQ 10.40625 5.953125 10.40625 10.109375 \nL 10.40625 50.734375 \nQ 10.40625 58.296875 10.0625 60.03125 \nQ 9.71875 61.765625 8.953125 62.390625 \nQ 8.203125 63.03125 7.03125 63.03125 \nQ 5.765625 63.03125 3.8125 62.25 \nL 2.984375 63.96875 \nL 16.3125 69.4375 \nz\n\" id=\"TimesNewRomanPSMT-6c\"/>\n     <path d=\"M 4.046875 26.125 \nL 29.296875 26.125 \nL 29.296875 18.75 \nL 4.046875 18.75 \nz\n\" id=\"TimesNewRomanPSMT-2d\"/>\n     <path d=\"M 1.3125 44.734375 \nL 22.359375 44.734375 \nL 22.359375 42.921875 \nQ 20.359375 42.921875 19.546875 42.234375 \nQ 18.75 41.546875 18.75 40.4375 \nQ 18.75 39.265625 20.453125 36.8125 \nQ 21 36.03125 22.078125 34.375 \nL 25.25 29.296875 \nL 28.90625 34.375 \nQ 32.421875 39.203125 32.421875 40.484375 \nQ 32.421875 41.5 31.59375 42.203125 \nQ 30.765625 42.921875 28.90625 42.921875 \nL 28.90625 44.734375 \nL 44.046875 44.734375 \nL 44.046875 42.921875 \nQ 41.65625 42.78125 39.890625 41.609375 \nQ 37.5 39.9375 33.34375 34.375 \nL 27.25 26.21875 \nL 38.375 10.203125 \nQ 42.484375 4.296875 44.234375 3.09375 \nQ 46 1.90625 48.78125 1.765625 \nL 48.78125 0 \nL 27.6875 0 \nL 27.6875 1.765625 \nQ 29.890625 1.765625 31.109375 2.734375 \nQ 32.03125 3.421875 32.03125 4.546875 \nQ 32.03125 5.671875 28.90625 10.203125 \nL 22.359375 19.78125 \nL 15.1875 10.203125 \nQ 11.859375 5.765625 11.859375 4.9375 \nQ 11.859375 3.765625 12.953125 2.8125 \nQ 14.0625 1.859375 16.265625 1.765625 \nL 16.265625 0 \nL 1.65625 0 \nL 1.65625 1.765625 \nQ 3.421875 2 4.734375 2.984375 \nQ 6.59375 4.390625 10.984375 10.203125 \nL 20.359375 22.65625 \nL 11.859375 34.96875 \nQ 8.25 40.234375 6.265625 41.578125 \nQ 4.296875 42.921875 1.3125 42.921875 \nz\n\" id=\"TimesNewRomanPSMT-78\"/>\n     <path d=\"M 14.5 69.4375 \nQ 16.546875 69.4375 17.984375 67.984375 \nQ 19.4375 66.546875 19.4375 64.5 \nQ 19.4375 62.453125 17.984375 60.984375 \nQ 16.546875 59.515625 14.5 59.515625 \nQ 12.453125 59.515625 10.984375 60.984375 \nQ 9.515625 62.453125 9.515625 64.5 \nQ 9.515625 66.546875 10.953125 67.984375 \nQ 12.40625 69.4375 14.5 69.4375 \nz\nM 18.5625 46.046875 \nL 18.5625 10.109375 \nQ 18.5625 5.90625 19.171875 4.515625 \nQ 19.78125 3.125 20.96875 2.4375 \nQ 22.171875 1.765625 25.34375 1.765625 \nL 25.34375 0 \nL 3.609375 0 \nL 3.609375 1.765625 \nQ 6.890625 1.765625 8 2.390625 \nQ 9.125 3.03125 9.78125 4.484375 \nQ 10.453125 5.953125 10.453125 10.109375 \nL 10.453125 27.34375 \nQ 10.453125 34.625 10.015625 36.765625 \nQ 9.671875 38.328125 8.9375 38.9375 \nQ 8.203125 39.546875 6.9375 39.546875 \nQ 5.5625 39.546875 3.609375 38.8125 \nL 2.9375 40.578125 \nL 16.40625 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-69\"/>\n     <path d=\"M 16.15625 36.578125 \nQ 24.03125 46.046875 31.15625 46.046875 \nQ 34.8125 46.046875 37.453125 44.21875 \nQ 40.09375 42.390625 41.65625 38.1875 \nQ 42.71875 35.25 42.71875 29.203125 \nL 42.71875 10.109375 \nQ 42.71875 5.859375 43.40625 4.34375 \nQ 43.953125 3.125 45.140625 2.4375 \nQ 46.34375 1.765625 49.5625 1.765625 \nL 49.5625 0 \nL 27.4375 0 \nL 27.4375 1.765625 \nL 28.375 1.765625 \nQ 31.5 1.765625 32.734375 2.703125 \nQ 33.984375 3.65625 34.46875 5.515625 \nQ 34.671875 6.25 34.671875 10.109375 \nL 34.671875 28.421875 \nQ 34.671875 34.515625 33.078125 37.28125 \nQ 31.5 40.046875 27.734375 40.046875 \nQ 21.921875 40.046875 16.15625 33.6875 \nL 16.15625 10.109375 \nQ 16.15625 5.5625 16.703125 4.5 \nQ 17.390625 3.078125 18.578125 2.421875 \nQ 19.78125 1.765625 23.4375 1.765625 \nL 23.4375 0 \nL 1.3125 0 \nL 1.3125 1.765625 \nL 2.296875 1.765625 \nQ 5.71875 1.765625 6.90625 3.484375 \nQ 8.109375 5.21875 8.109375 10.109375 \nL 8.109375 26.703125 \nQ 8.109375 34.765625 7.734375 36.515625 \nQ 7.375 38.28125 6.609375 38.90625 \nQ 5.859375 39.546875 4.59375 39.546875 \nQ 3.21875 39.546875 1.3125 38.8125 \nL 0.59375 40.578125 \nL 14.0625 46.046875 \nL 16.15625 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-6e\"/>\n     <path d=\"M -0.09375 40.28125 \nL 13.671875 45.84375 \nL 15.53125 45.84375 \nL 15.53125 35.40625 \nQ 19 41.3125 22.484375 43.671875 \nQ 25.984375 46.046875 29.828125 46.046875 \nQ 36.578125 46.046875 41.0625 40.765625 \nQ 46.578125 34.328125 46.578125 23.96875 \nQ 46.578125 12.40625 39.9375 4.828125 \nQ 34.46875 -1.375 26.171875 -1.375 \nQ 22.5625 -1.375 19.921875 -0.34375 \nQ 17.96875 0.390625 15.53125 2.59375 \nL 15.53125 -11.03125 \nQ 15.53125 -15.625 16.09375 -16.859375 \nQ 16.65625 -18.109375 18.046875 -18.84375 \nQ 19.4375 -19.578125 23.09375 -19.578125 \nL 23.09375 -21.390625 \nL -0.34375 -21.390625 \nL -0.34375 -19.578125 \nL 0.875 -19.578125 \nQ 3.5625 -19.625 5.46875 -18.5625 \nQ 6.390625 -18.015625 6.90625 -16.8125 \nQ 7.421875 -15.625 7.421875 -10.75 \nL 7.421875 31.546875 \nQ 7.421875 35.890625 7.03125 37.0625 \nQ 6.640625 38.234375 5.78125 38.8125 \nQ 4.9375 39.40625 3.46875 39.40625 \nQ 2.296875 39.40625 0.484375 38.71875 \nz\nM 15.53125 32.515625 \nL 15.53125 15.828125 \nQ 15.53125 10.40625 15.96875 8.6875 \nQ 16.65625 5.859375 19.3125 3.703125 \nQ 21.96875 1.5625 26.03125 1.5625 \nQ 30.90625 1.5625 33.9375 5.375 \nQ 37.890625 10.359375 37.890625 19.390625 \nQ 37.890625 29.640625 33.40625 35.15625 \nQ 30.28125 38.96875 25.984375 38.96875 \nQ 23.640625 38.96875 21.34375 37.796875 \nQ 19.578125 36.921875 15.53125 32.515625 \nz\n\" id=\"TimesNewRomanPSMT-70\"/>\n     <path d=\"M 20.609375 41.21875 \nL 20.609375 11.8125 \nQ 20.609375 5.5625 21.96875 3.90625 \nQ 23.78125 1.765625 26.8125 1.765625 \nL 30.859375 1.765625 \nL 30.859375 0 \nL 4.15625 0 \nL 4.15625 1.765625 \nL 6.15625 1.765625 \nQ 8.109375 1.765625 9.71875 2.734375 \nQ 11.328125 3.71875 11.9375 5.375 \nQ 12.546875 7.03125 12.546875 11.8125 \nL 12.546875 41.21875 \nL 3.859375 41.21875 \nL 3.859375 44.734375 \nL 12.546875 44.734375 \nL 12.546875 47.65625 \nQ 12.546875 54.34375 14.6875 58.984375 \nQ 16.84375 63.625 21.265625 66.484375 \nQ 25.6875 69.34375 31.203125 69.34375 \nQ 36.328125 69.34375 40.625 66.015625 \nQ 43.453125 63.8125 43.453125 61.078125 \nQ 43.453125 59.625 42.1875 58.328125 \nQ 40.921875 57.03125 39.453125 57.03125 \nQ 38.328125 57.03125 37.078125 57.828125 \nQ 35.84375 58.640625 34.03125 61.296875 \nQ 32.234375 63.96875 30.71875 64.890625 \nQ 29.203125 65.828125 27.34375 65.828125 \nQ 25.09375 65.828125 23.53125 64.625 \nQ 21.96875 63.421875 21.28125 60.90625 \nQ 20.609375 58.40625 20.609375 47.953125 \nL 20.609375 44.734375 \nL 32.125 44.734375 \nL 32.125 41.21875 \nz\n\" id=\"TimesNewRomanPSMT-66\"/>\n     <path d=\"M 0.640625 44.734375 \nL 19.390625 44.734375 \nL 19.390625 42.921875 \nQ 16.796875 42.71875 15.984375 41.984375 \nQ 15.1875 41.265625 15.1875 39.890625 \nQ 15.1875 38.375 16.015625 36.234375 \nL 25.59375 10.5 \nL 35.203125 31.453125 \nL 32.671875 38.03125 \nQ 31.5 40.96875 29.59375 42.09375 \nQ 28.515625 42.78125 25.59375 42.921875 \nL 25.59375 44.734375 \nL 46.875 44.734375 \nL 46.875 42.921875 \nQ 43.359375 42.78125 41.890625 41.65625 \nQ 40.921875 40.875 40.921875 39.15625 \nQ 40.921875 38.1875 41.3125 37.15625 \nL 51.46875 11.46875 \nL 60.890625 36.234375 \nQ 61.859375 38.875 61.859375 40.4375 \nQ 61.859375 41.359375 60.90625 42.09375 \nQ 59.96875 42.828125 57.171875 42.921875 \nL 57.171875 44.734375 \nL 71.296875 44.734375 \nL 71.296875 42.921875 \nQ 67.046875 42.28125 65.046875 37.15625 \nL 50.09375 -1.375 \nL 48.09375 -1.375 \nL 36.921875 27.203125 \nL 23.875 -1.375 \nL 22.078125 -1.375 \nL 7.71875 36.234375 \nQ 6.296875 39.796875 4.921875 41.03125 \nQ 3.5625 42.28125 0.640625 42.921875 \nz\n\" id=\"TimesNewRomanPSMT-77\"/>\n     <path d=\"M 16.265625 69.4375 \nL 16.265625 36.71875 \nQ 21.6875 42.671875 24.859375 44.359375 \nQ 28.03125 46.046875 31.203125 46.046875 \nQ 35.015625 46.046875 37.75 43.9375 \nQ 40.484375 41.84375 41.796875 37.359375 \nQ 42.71875 34.234375 42.71875 25.921875 \nL 42.71875 10.109375 \nQ 42.71875 5.859375 43.40625 4.296875 \nQ 43.890625 3.125 45.0625 2.4375 \nQ 46.234375 1.765625 49.359375 1.765625 \nL 49.359375 0 \nL 27.390625 0 \nL 27.390625 1.765625 \nL 28.421875 1.765625 \nQ 31.546875 1.765625 32.765625 2.703125 \nQ 33.984375 3.65625 34.46875 5.515625 \nQ 34.625 6.296875 34.625 10.109375 \nL 34.625 25.921875 \nQ 34.625 33.25 33.859375 35.546875 \nQ 33.109375 37.84375 31.4375 38.984375 \nQ 29.78125 40.140625 27.4375 40.140625 \nQ 25.046875 40.140625 22.453125 38.859375 \nQ 19.875 37.59375 16.265625 33.734375 \nL 16.265625 10.109375 \nQ 16.265625 5.515625 16.765625 4.390625 \nQ 17.28125 3.265625 18.671875 2.515625 \nQ 20.0625 1.765625 23.484375 1.765625 \nL 23.484375 0 \nL 1.3125 0 \nL 1.3125 1.765625 \nQ 4.296875 1.765625 6 2.6875 \nQ 6.984375 3.171875 7.5625 4.53125 \nQ 8.15625 5.90625 8.15625 10.109375 \nL 8.15625 50.59375 \nQ 8.15625 58.25 7.78125 60 \nQ 7.421875 61.765625 6.65625 62.390625 \nQ 5.90625 63.03125 4.640625 63.03125 \nQ 3.609375 63.03125 1.3125 62.25 \nL 0.640625 63.96875 \nL 14.015625 69.4375 \nz\n\" id=\"TimesNewRomanPSMT-68\"/>\n     <path d=\"M 34.71875 5.03125 \nQ 31.453125 1.609375 28.328125 0.109375 \nQ 25.203125 -1.375 21.578125 -1.375 \nQ 14.265625 -1.375 8.796875 4.75 \nQ 3.328125 10.890625 3.328125 20.515625 \nQ 3.328125 30.125 9.375 38.109375 \nQ 15.4375 46.09375 24.953125 46.09375 \nQ 30.859375 46.09375 34.71875 42.328125 \nL 34.71875 50.59375 \nQ 34.71875 58.25 34.34375 60 \nQ 33.984375 61.765625 33.203125 62.390625 \nQ 32.421875 63.03125 31.25 63.03125 \nQ 29.984375 63.03125 27.875 62.25 \nL 27.25 63.96875 \nL 40.578125 69.4375 \nL 42.78125 69.4375 \nL 42.78125 17.71875 \nQ 42.78125 9.859375 43.140625 8.125 \nQ 43.5 6.390625 44.3125 5.703125 \nQ 45.125 5.03125 46.1875 5.03125 \nQ 47.515625 5.03125 49.703125 5.859375 \nL 50.25 4.15625 \nL 36.96875 -1.375 \nL 34.71875 -1.375 \nz\nM 34.71875 8.453125 \nL 34.71875 31.5 \nQ 34.421875 34.8125 32.953125 37.546875 \nQ 31.5 40.28125 29.078125 41.671875 \nQ 26.65625 43.0625 24.359375 43.0625 \nQ 20.0625 43.0625 16.703125 39.203125 \nQ 12.25 34.125 12.25 24.359375 \nQ 12.25 14.5 16.546875 9.25 \nQ 20.84375 4 26.125 4 \nQ 30.5625 4 34.71875 8.453125 \nz\n\" id=\"TimesNewRomanPSMT-64\"/>\n     <path d=\"M 15.09375 16.3125 \nQ 10.984375 18.3125 8.78125 21.890625 \nQ 6.59375 25.484375 6.59375 29.828125 \nQ 6.59375 36.46875 11.59375 41.25 \nQ 16.609375 46.046875 24.421875 46.046875 \nQ 30.8125 46.046875 35.5 42.921875 \nL 44.96875 42.921875 \nQ 47.078125 42.921875 47.40625 42.796875 \nQ 47.75 42.671875 47.90625 42.390625 \nQ 48.1875 41.9375 48.1875 40.828125 \nQ 48.1875 39.546875 47.953125 39.0625 \nQ 47.796875 38.8125 47.4375 38.671875 \nQ 47.078125 38.53125 44.96875 38.53125 \nL 39.15625 38.53125 \nQ 41.890625 35.015625 41.890625 29.546875 \nQ 41.890625 23.296875 37.109375 18.84375 \nQ 32.328125 14.40625 24.265625 14.40625 \nQ 20.953125 14.40625 17.484375 15.375 \nQ 15.328125 13.53125 14.5625 12.140625 \nQ 13.8125 10.75 13.8125 9.765625 \nQ 13.8125 8.9375 14.625 8.15625 \nQ 15.4375 7.375 17.78125 7.03125 \nQ 19.140625 6.84375 24.609375 6.6875 \nQ 34.671875 6.453125 37.640625 6 \nQ 42.1875 5.375 44.890625 2.640625 \nQ 47.609375 -0.09375 47.609375 -4.109375 \nQ 47.609375 -9.625 42.4375 -14.453125 \nQ 34.8125 -21.578125 22.5625 -21.578125 \nQ 13.140625 -21.578125 6.640625 -17.328125 \nQ 2.984375 -14.890625 2.984375 -12.25 \nQ 2.984375 -11.078125 3.515625 -9.90625 \nQ 4.34375 -8.109375 6.9375 -4.890625 \nQ 7.28125 -4.4375 11.921875 0.390625 \nQ 9.375 1.90625 8.328125 3.09375 \nQ 7.28125 4.296875 7.28125 5.8125 \nQ 7.28125 7.515625 8.671875 9.8125 \nQ 10.0625 12.109375 15.09375 16.3125 \nz\nM 23.578125 43.703125 \nQ 19.96875 43.703125 17.53125 40.8125 \nQ 15.09375 37.9375 15.09375 31.984375 \nQ 15.09375 24.265625 18.40625 20.015625 \nQ 20.953125 16.796875 24.859375 16.796875 \nQ 28.5625 16.796875 30.953125 19.578125 \nQ 33.34375 22.359375 33.34375 28.328125 \nQ 33.34375 36.078125 29.984375 40.484375 \nQ 27.484375 43.703125 23.578125 43.703125 \nz\nM 14.59375 0 \nQ 12.3125 -2.484375 11.140625 -4.625 \nQ 9.96875 -6.78125 9.96875 -8.59375 \nQ 9.96875 -10.9375 12.796875 -12.703125 \nQ 17.671875 -15.71875 26.90625 -15.71875 \nQ 35.6875 -15.71875 39.859375 -12.609375 \nQ 44.046875 -9.515625 44.046875 -6 \nQ 44.046875 -3.46875 41.546875 -2.390625 \nQ 39.015625 -1.3125 31.5 -1.125 \nQ 20.515625 -0.828125 14.59375 0 \nz\n\" id=\"TimesNewRomanPSMT-67\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(7.2 21.0875)scale(0.2 -0.2)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-54\"/>\n     <use x=\"60.974609\" xlink:href=\"#TimesNewRomanPSMT-6f\"/>\n     <use x=\"110.974609\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n     <use x=\"138.757812\" xlink:href=\"#TimesNewRomanPSMT-61\"/>\n     <use x=\"183.142578\" xlink:href=\"#TimesNewRomanPSMT-6c\"/>\n     <use x=\"210.925781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"235.925781\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"269.226562\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"313.611328\" xlink:href=\"#TimesNewRomanPSMT-2d\"/>\n     <use x=\"346.912109\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"391.296875\" xlink:href=\"#TimesNewRomanPSMT-78\"/>\n     <use x=\"441.296875\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"485.681641\" xlink:href=\"#TimesNewRomanPSMT-63\"/>\n     <use x=\"530.066406\" xlink:href=\"#TimesNewRomanPSMT-75\"/>\n     <use x=\"580.066406\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n     <use x=\"607.849609\" xlink:href=\"#TimesNewRomanPSMT-69\"/>\n     <use x=\"635.632812\" xlink:href=\"#TimesNewRomanPSMT-6f\"/>\n     <use x=\"685.632812\" xlink:href=\"#TimesNewRomanPSMT-6e\"/>\n     <use x=\"735.632812\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"760.632812\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"793.933594\" xlink:href=\"#TimesNewRomanPSMT-61\"/>\n     <use x=\"838.318359\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n     <use x=\"866.101562\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"910.486328\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"935.486328\" xlink:href=\"#TimesNewRomanPSMT-70\"/>\n     <use x=\"985.486328\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"1029.871094\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"1063.171875\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"1088.171875\" xlink:href=\"#TimesNewRomanPSMT-66\"/>\n     <use x=\"1121.472656\" xlink:href=\"#TimesNewRomanPSMT-69\"/>\n     <use x=\"1149.255859\" xlink:href=\"#TimesNewRomanPSMT-6c\"/>\n     <use x=\"1177.039062\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"1221.423828\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"1246.423828\" xlink:href=\"#TimesNewRomanPSMT-77\"/>\n     <use x=\"1318.640625\" xlink:href=\"#TimesNewRomanPSMT-69\"/>\n     <use x=\"1346.423828\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n     <use x=\"1374.207031\" xlink:href=\"#TimesNewRomanPSMT-68\"/>\n     <use x=\"1424.207031\" xlink:href=\"#TimesNewRomanPSMT-6f\"/>\n     <use x=\"1474.207031\" xlink:href=\"#TimesNewRomanPSMT-75\"/>\n     <use x=\"1524.207031\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n     <use x=\"1551.990234\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"1576.990234\" xlink:href=\"#TimesNewRomanPSMT-63\"/>\n     <use x=\"1621.375\" xlink:href=\"#TimesNewRomanPSMT-6f\"/>\n     <use x=\"1671.375\" xlink:href=\"#TimesNewRomanPSMT-64\"/>\n     <use x=\"1721.375\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"1765.759766\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"1790.759766\" xlink:href=\"#TimesNewRomanPSMT-63\"/>\n     <use x=\"1835.144531\" xlink:href=\"#TimesNewRomanPSMT-6c\"/>\n     <use x=\"1862.927734\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"1907.3125\" xlink:href=\"#TimesNewRomanPSMT-61\"/>\n     <use x=\"1951.697266\" xlink:href=\"#TimesNewRomanPSMT-6e\"/>\n     <use x=\"2001.697266\" xlink:href=\"#TimesNewRomanPSMT-69\"/>\n     <use x=\"2029.480469\" xlink:href=\"#TimesNewRomanPSMT-6e\"/>\n     <use x=\"2079.480469\" xlink:href=\"#TimesNewRomanPSMT-67\"/>\n    </g>\n   </g>\n  </g>\n </g>\n <defs>\n  <clipPath id=\"p9772d2f126\">\n   <rect height=\"229.94\" width=\"304.505625\" x=\"67.89875\" y=\"27.0875\"/>\n  </clipPath>\n </defs>\n</svg>\n",
      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def make_autopct(values):\n",
    "    def my_autopct(pct):\n",
    "        total = sum(values)\n",
    "        val = int(round(pct*total/100.0))\n",
    "        return '{p:.2f}%  ({v:d})'.format(p=pct,v=val)\n",
    "    return my_autopct\n",
    "\n",
    "def get_success_rates(df):\n",
    "    print \"Total number of entries: \"+ str(len(df))\n",
    "    print \"Total number after bad DOIs are removed: \"+ str(len(df))\n",
    "    \n",
    "    print \"Unique DOIs: \"+ str(len(df['doi'].unique()))\n",
    "    \n",
    "    # calculate success\n",
    "    success = (df['result'] == 'success').sum()\n",
    "    print \"Success: \" + str(success)+ \" out of \" + str(len(df)) +\" => \"+ str(success*1.0/len(df))\n",
    "    \n",
    "    til = (df['result'] == 'time limit exceeded').sum()\n",
    "    print \"TIL: \" + str(til)+ \" out of \" + str(len(df)) +\" => \"+ str(til*1.0/len(df))\n",
    "    \n",
    "    error = len(df)-til-success\n",
    "    print \"Error: \" + str(error)+ \" out of \" + str(len(df)) +\" => \"+ str(error*1.0/len(df))\n",
    "    \n",
    "    return [error, success]\n",
    "\n",
    "def plot_code(df, plot_title, plot_name, aggregation=False):\n",
    "    labels = ['Error', 'Success']\n",
    "    if aggregation:\n",
    "        sizes = get_aggregated(df)\n",
    "    else:\n",
    "        sizes = get_success_rates(df)\n",
    "     \n",
    "    fig1, ax1 = plt.subplots()\n",
    "    plt.rcParams['font.size'] = 16\n",
    "    ax1.pie(sizes, labels=labels, autopct=make_autopct(sizes), startangle=40,  \\\n",
    "            textprops={'fontsize': 14},wedgeprops={'alpha':0.6})\n",
    "\n",
    "    #draw circle\n",
    "    centre_circle = plt.Circle((0,0),0.70,fc='white')\n",
    "\n",
    "    fig = plt.gcf()\n",
    "    fig.gca().add_artist(centre_circle)\n",
    "\n",
    "    # Equal aspect ratio ensures that pie is drawn as a circle\n",
    "    ax1.axis('equal')  \n",
    "    plt.title(plot_title, size=20)\n",
    "    plt.tight_layout()\n",
    "\n",
    "    plt.show()\n",
    "    fig1.savefig(\"plots/{}\".format(plot_name), dpi=100)\n",
    "    \n",
    "dfe = df[df.result.notnull()]\n",
    "plot_code(dfe, \"Total re-execution rate per file without code cleaning\", \"aggregated_no_env.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Validation test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(df1,df2,on=['doi','file'], how='outer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>doi</th>\n      <th>file</th>\n      <th>r32_x</th>\n      <th>r36_x</th>\n      <th>r40_x</th>\n      <th>result_x</th>\n      <th>success_x</th>\n      <th>r32_y</th>\n      <th>r36_y</th>\n      <th>r40_y</th>\n      <th>result_y</th>\n      <th>success_y</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>doi:10.7910/DVN/XFQZI2</td>\n      <td>Condemnation.R</td>\n      <td>Error in eval(expr, envir, enclos) : could not...</td>\n      <td>Error in read.dta13('Condemnation.dta') :   co...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Error in library(readstata13) : there is no pa...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>doi:10.7910/DVN/WGPDBS</td>\n      <td>Replication_of_Figures.R</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_10_effect_of_winning_on_gov.R</td>\n      <td>Error in diag(vcovHC(DMareg, type = 'HC3')) : ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>0.0</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_11_rd_placebo.R</td>\n      <td>Error in ggsave('placebo.pdf', plot = placebo,...</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>Error in library(gridExtra) : there is no pack...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_12_historical_trend.R</td>\n      <td>Error in ggsave('historical_trend.pdf', plot =...</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n      <td>Error in library(ggthemes) : there is no packa...</td>\n      <td>NaN</td>\n      <td>Error in library(ggthemes) : there is no packa...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                      doi                               file  \\\n0  doi:10.7910/DVN/XFQZI2                     Condemnation.R   \n1  doi:10.7910/DVN/WGPDBS           Replication_of_Figures.R   \n2  doi:10.7910/DVN/BPON3K  fig_10_effect_of_winning_on_gov.R   \n3  doi:10.7910/DVN/BPON3K                fig_11_rd_placebo.R   \n4  doi:10.7910/DVN/BPON3K          fig_12_historical_trend.R   \n\n                                               r32_x  \\\n0  Error in eval(expr, envir, enclos) : could not...   \n1                                            success   \n2  Error in diag(vcovHC(DMareg, type = 'HC3')) : ...   \n3  Error in ggsave('placebo.pdf', plot = placebo,...   \n4  Error in ggsave('historical_trend.pdf', plot =...   \n\n                                               r36_x  \\\n0  Error in read.dta13('Condemnation.dta') :   co...   \n1                                            success   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...   \n3                                            success   \n4                                            success   \n\n                                               r40_x  \\\n0                                                NaN   \n1                                            success   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...   \n3                                            success   \n4                                            success   \n\n                                            result_x  success_x  \\\n0                                                NaN        NaN   \n1                                            success        1.0   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...        0.0   \n3                                            success        1.0   \n4                                            success        1.0   \n\n                                               r32_y    r36_y  \\\n0  Error in library(readstata13) : there is no pa...      NaN   \n1                                            success  success   \n2  Error in library(gridExtra) : there is no pack...      NaN   \n3  Error in library(gridExtra) : there is no pack...      NaN   \n4  Error in library(ggthemes) : there is no packa...      NaN   \n\n                                               r40_y result_y  success_y  \n0                                                NaN      NaN        NaN  \n1                                            success  success        1.0  \n2  Error in library(gridExtra) : there is no pack...      NaN        NaN  \n3  Error in library(gridExtra) : there is no pack...      NaN        NaN  \n4  Error in library(ggthemes) : there is no packa...      NaN        NaN  "
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "843\n"
    }
   ],
   "source": [
    "print(len(df[(df['success_x'] == 1) & (df['success_y'] == 1)]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "4779"
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df[(df['success_y'].isnull())])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "8609"
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Aggregated per dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"data/aggregate_results_env.csv\", index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>doi</th>\n      <th>file</th>\n      <th>r32</th>\n      <th>r36</th>\n      <th>r40</th>\n      <th>result</th>\n      <th>success</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>doi:10.7910/DVN/XFQZI2</td>\n      <td>Condemnation.R</td>\n      <td>Error in eval(expr, envir, enclos) : could not...</td>\n      <td>Error in read.dta13('Condemnation.dta') :   co...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>doi:10.7910/DVN/WGPDBS</td>\n      <td>Replication_of_Figures.R</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_10_effect_of_winning_on_gov.R</td>\n      <td>Error in diag(vcovHC(DMareg, type = 'HC3')) : ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_11_rd_placebo.R</td>\n      <td>Error in ggsave('placebo.pdf', plot = placebo,...</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_12_historical_trend.R</td>\n      <td>Error in ggsave('historical_trend.pdf', plot =...</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                      doi                               file  \\\n0  doi:10.7910/DVN/XFQZI2                     Condemnation.R   \n1  doi:10.7910/DVN/WGPDBS           Replication_of_Figures.R   \n2  doi:10.7910/DVN/BPON3K  fig_10_effect_of_winning_on_gov.R   \n3  doi:10.7910/DVN/BPON3K                fig_11_rd_placebo.R   \n4  doi:10.7910/DVN/BPON3K          fig_12_historical_trend.R   \n\n                                                 r32  \\\n0  Error in eval(expr, envir, enclos) : could not...   \n1                                            success   \n2  Error in diag(vcovHC(DMareg, type = 'HC3')) : ...   \n3  Error in ggsave('placebo.pdf', plot = placebo,...   \n4  Error in ggsave('historical_trend.pdf', plot =...   \n\n                                                 r36  \\\n0  Error in read.dta13('Condemnation.dta') :   co...   \n1                                            success   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...   \n3                                            success   \n4                                            success   \n\n                                                 r40  \\\n0                                                NaN   \n1                                            success   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...   \n3                                            success   \n4                                            success   \n\n                                              result  success  \n0                                                NaN      NaN  \n1                                            success      1.0  \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...      0.0  \n3                                            success      1.0  \n4                                            success      1.0  "
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_code(sizes, plot_title, plot_name):\n",
    "    labels = ['Error', 'Success']\n",
    "   \n",
    "    fig1, ax1 = plt.subplots()\n",
    "    plt.rcParams['font.size'] = 16\n",
    "    ax1.pie(sizes, labels=labels, autopct=make_autopct(sizes), startangle=40,  \\\n",
    "            textprops={'fontsize': 14},wedgeprops={'alpha':0.6})\n",
    "\n",
    "    #draw circle\n",
    "    centre_circle = plt.Circle((0,0),0.70,fc='white')\n",
    "\n",
    "    fig = plt.gcf()\n",
    "    fig.gca().add_artist(centre_circle)\n",
    "\n",
    "    # Equal aspect ratio ensures that pie is drawn as a circle\n",
    "    ax1.axis('equal')  \n",
    "    plt.title(plot_title, size=20)\n",
    "    plt.tight_layout()\n",
    "\n",
    "    plt.show()\n",
    "    fig1.savefig(\"plots/{}\".format(plot_name), dpi=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "3695"
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df.loc[~df['result'].isnull()].copy()\n",
    "len(df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>doi</th>\n      <th>file</th>\n      <th>r32</th>\n      <th>r36</th>\n      <th>r40</th>\n      <th>result</th>\n      <th>success</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>doi:10.7910/DVN/WGPDBS</td>\n      <td>Replication_of_Figures.R</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_10_effect_of_winning_on_gov.R</td>\n      <td>Error in diag(vcovHC(DMareg, type = 'HC3')) : ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_11_rd_placebo.R</td>\n      <td>Error in ggsave('placebo.pdf', plot = placebo,...</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_12_historical_trend.R</td>\n      <td>Error in ggsave('historical_trend.pdf', plot =...</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_13_plot_loyalty_df_pct.R</td>\n      <td>Error in data.table(x) : object 'x' not found</td>\n      <td>Error in data.table(x) : object 'x' not found</td>\n      <td>Error in data.table(x) : object 'x' not found</td>\n      <td>Error in data.table(x) : object 'x' not found</td>\n      <td>0.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                      doi                               file  \\\n1  doi:10.7910/DVN/WGPDBS           Replication_of_Figures.R   \n2  doi:10.7910/DVN/BPON3K  fig_10_effect_of_winning_on_gov.R   \n3  doi:10.7910/DVN/BPON3K                fig_11_rd_placebo.R   \n4  doi:10.7910/DVN/BPON3K          fig_12_historical_trend.R   \n5  doi:10.7910/DVN/BPON3K       fig_13_plot_loyalty_df_pct.R   \n\n                                                 r32  \\\n1                                            success   \n2  Error in diag(vcovHC(DMareg, type = 'HC3')) : ...   \n3  Error in ggsave('placebo.pdf', plot = placebo,...   \n4  Error in ggsave('historical_trend.pdf', plot =...   \n5      Error in data.table(x) : object 'x' not found   \n\n                                                 r36  \\\n1                                            success   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...   \n3                                            success   \n4                                            success   \n5      Error in data.table(x) : object 'x' not found   \n\n                                                 r40  \\\n1                                            success   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...   \n3                                            success   \n4                                            success   \n5      Error in data.table(x) : object 'x' not found   \n\n                                              result  success  \n1                                            success      1.0  \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...      0.0  \n3                                            success      1.0  \n4                                            success      1.0  \n5      Error in data.table(x) : object 'x' not found      0.0  "
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "1447"
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ag_tot = set(df2['doi'].unique().tolist())\n",
    "len(ag_tot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "648"
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ag_suc = set(df2[df2.result == 'success']['doi'].unique().tolist())\n",
    "len(ag_suc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Created with matplotlib (http://matplotlib.org/) -->\n<svg height=\"267.7275pt\" version=\"1.1\" viewBox=\"0 0 411.84 267.7275\" width=\"411.84pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <defs>\n  <style type=\"text/css\">\n*{stroke-linecap:butt;stroke-linejoin:round;}\n  </style>\n </defs>\n <g id=\"figure_1\">\n  <g id=\"patch_1\">\n   <path d=\"M 0 267.7275 \nL 411.84 267.7275 \nL 411.84 0 \nL 0 0 \nz\n\" style=\"fill:none;\"/>\n  </g>\n  <g id=\"axes_1\">\n   <g id=\"matplotlib.axis_1\"/>\n   <g id=\"matplotlib.axis_2\"/>\n   <g id=\"patch_2\">\n    <path d=\"M 285.443947 74.480386 \nC 275.817408 63.007923 263.807864 53.767333 250.251626 47.402107 \nC 236.695389 41.03688 221.914611 37.698281 206.938585 37.6188 \nC 191.962559 37.539318 177.147177 40.720844 163.524142 46.941823 \nC 149.901107 53.162802 137.794158 62.2754 128.04639 73.645039 \nC 118.298622 85.014678 111.141681 98.371169 107.073959 112.784403 \nC 103.006237 127.197636 102.124398 142.325095 104.489852 157.113344 \nC 106.855306 171.901593 112.411839 185.999202 120.77251 198.424452 \nC 129.133182 210.849703 140.099307 221.30732 152.907234 229.069063 \nL 206.390905 140.813765 \nL 285.443947 74.480386 \nz\n\" style=\"fill:#1f77b4;opacity:0.6;stroke:#ffffff;stroke-linejoin:miter;\"/>\n   </g>\n   <g id=\"patch_3\">\n    <path d=\"M 152.907234 229.069063 \nC 173.812179 241.737687 198.553278 246.575682 222.690479 242.714818 \nC 246.82768 238.853954 268.825222 226.539884 284.735413 207.982498 \nC 300.645604 189.425112 309.456138 165.805148 309.58587 141.36146 \nC 309.715602 116.917771 301.156278 93.205619 285.44396 74.4804 \nL 206.390905 140.813765 \nL 152.907234 229.069063 \nz\n\" style=\"fill:#ff7f0e;opacity:0.6;stroke:#ffffff;stroke-linejoin:miter;\"/>\n   </g>\n   <g id=\"patch_4\">\n    <path clip-path=\"url(#p2ee97d3736)\" d=\"M 206.390905 213.051257 \nC 225.548512 213.051257 243.924052 205.43986 257.470526 191.893386 \nC 271.017 178.346912 278.628397 159.971372 278.628397 140.813765 \nC 278.628397 121.656158 271.017 103.280617 257.470526 89.734144 \nC 243.924052 76.18767 225.548512 68.576272 206.390905 68.576272 \nC 187.233298 68.576272 168.857757 76.18767 155.311284 89.734144 \nC 141.76481 103.280617 134.153412 121.656158 134.153412 140.813765 \nC 134.153412 159.971372 141.76481 178.346912 155.311284 191.893386 \nC 168.857757 205.43986 187.233298 213.051257 206.390905 213.051257 \nz\n\" style=\"fill:#ffffff;stroke:#ffffff;stroke-linejoin:miter;\"/>\n   </g>\n   <g id=\"text_1\">\n    <!-- Error -->\n    <defs>\n     <path d=\"M 20.90625 62.59375 \nL 20.90625 36.421875 \nL 35.453125 36.421875 \nQ 41.109375 36.421875 43.015625 38.140625 \nQ 45.5625 40.375 45.84375 46.046875 \nL 47.65625 46.046875 \nL 47.65625 23 \nL 45.84375 23 \nQ 45.171875 27.828125 44.484375 29.203125 \nQ 43.609375 30.90625 41.59375 31.875 \nQ 39.59375 32.859375 35.453125 32.859375 \nL 20.90625 32.859375 \nL 20.90625 11.03125 \nQ 20.90625 6.640625 21.296875 5.6875 \nQ 21.6875 4.734375 22.65625 4.171875 \nQ 23.640625 3.609375 26.375 3.609375 \nL 37.59375 3.609375 \nQ 43.21875 3.609375 45.75 4.390625 \nQ 48.296875 5.171875 50.640625 7.46875 \nQ 53.65625 10.5 56.84375 16.609375 \nL 58.796875 16.609375 \nL 53.078125 0 \nL 2.046875 0 \nL 2.046875 1.8125 \nL 4.390625 1.8125 \nQ 6.734375 1.8125 8.84375 2.9375 \nQ 10.40625 3.71875 10.96875 5.28125 \nQ 11.53125 6.84375 11.53125 11.671875 \nL 11.53125 54.6875 \nQ 11.53125 60.984375 10.25 62.453125 \nQ 8.5 64.40625 4.390625 64.40625 \nL 2.046875 64.40625 \nL 2.046875 66.21875 \nL 53.078125 66.21875 \nL 53.8125 51.703125 \nL 51.90625 51.703125 \nQ 50.875 56.9375 49.625 58.890625 \nQ 48.390625 60.84375 45.953125 61.859375 \nQ 44 62.59375 39.0625 62.59375 \nz\n\" id=\"TimesNewRomanPSMT-45\"/>\n     <path d=\"M 16.21875 46.046875 \nL 16.21875 35.984375 \nQ 21.828125 46.046875 27.734375 46.046875 \nQ 30.421875 46.046875 32.171875 44.40625 \nQ 33.9375 42.78125 33.9375 40.625 \nQ 33.9375 38.71875 32.65625 37.390625 \nQ 31.390625 36.078125 29.640625 36.078125 \nQ 27.9375 36.078125 25.8125 37.765625 \nQ 23.6875 39.453125 22.65625 39.453125 \nQ 21.78125 39.453125 20.75 38.484375 \nQ 18.5625 36.46875 16.21875 31.890625 \nL 16.21875 10.453125 \nQ 16.21875 6.734375 17.140625 4.828125 \nQ 17.78125 3.515625 19.390625 2.640625 \nQ 21 1.765625 24.03125 1.765625 \nL 24.03125 0 \nL 1.125 0 \nL 1.125 1.765625 \nQ 4.546875 1.765625 6.203125 2.828125 \nQ 7.421875 3.609375 7.90625 5.328125 \nQ 8.15625 6.15625 8.15625 10.0625 \nL 8.15625 27.390625 \nQ 8.15625 35.203125 7.828125 36.6875 \nQ 7.515625 38.1875 6.65625 38.859375 \nQ 5.8125 39.546875 4.546875 39.546875 \nQ 3.03125 39.546875 1.125 38.8125 \nL 0.640625 40.578125 \nL 14.15625 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-72\"/>\n     <path d=\"M 25 46.046875 \nQ 35.15625 46.046875 41.3125 38.328125 \nQ 46.53125 31.734375 46.53125 23.1875 \nQ 46.53125 17.1875 43.640625 11.03125 \nQ 40.765625 4.890625 35.71875 1.75 \nQ 30.671875 -1.375 24.46875 -1.375 \nQ 14.359375 -1.375 8.40625 6.6875 \nQ 3.375 13.484375 3.375 21.921875 \nQ 3.375 28.078125 6.421875 34.15625 \nQ 9.46875 40.234375 14.453125 43.140625 \nQ 19.4375 46.046875 25 46.046875 \nz\nM 23.484375 42.875 \nQ 20.90625 42.875 18.28125 41.328125 \nQ 15.671875 39.796875 14.0625 35.9375 \nQ 12.453125 32.078125 12.453125 26.03125 \nQ 12.453125 16.265625 16.328125 9.171875 \nQ 20.21875 2.09375 26.5625 2.09375 \nQ 31.296875 2.09375 34.375 6 \nQ 37.453125 9.90625 37.453125 19.4375 \nQ 37.453125 31.34375 32.328125 38.1875 \nQ 28.859375 42.875 23.484375 42.875 \nz\n\" id=\"TimesNewRomanPSMT-6f\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(86.456938 70.771916)scale(0.16 -0.16)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-45\"/>\n     <use x=\"61.083984\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"94.384766\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"127.685547\" xlink:href=\"#TimesNewRomanPSMT-6f\"/>\n     <use x=\"177.685547\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n    </g>\n   </g>\n   <g id=\"text_2\">\n    <!-- 55.22%  (799) -->\n    <defs>\n     <path d=\"M 43.40625 66.21875 \nL 39.59375 57.90625 \nL 19.671875 57.90625 \nL 15.328125 49.03125 \nQ 28.265625 47.125 35.84375 39.40625 \nQ 42.328125 32.765625 42.328125 23.78125 \nQ 42.328125 18.5625 40.203125 14.109375 \nQ 38.09375 9.671875 34.859375 6.546875 \nQ 31.640625 3.421875 27.6875 1.515625 \nQ 22.078125 -1.171875 16.15625 -1.171875 \nQ 10.203125 -1.171875 7.484375 0.84375 \nQ 4.78125 2.875 4.78125 5.328125 \nQ 4.78125 6.6875 5.90625 7.734375 \nQ 7.03125 8.796875 8.734375 8.796875 \nQ 10.015625 8.796875 10.96875 8.40625 \nQ 11.921875 8.015625 14.203125 6.390625 \nQ 17.875 3.859375 21.625 3.859375 \nQ 27.34375 3.859375 31.65625 8.171875 \nQ 35.984375 12.5 35.984375 18.703125 \nQ 35.984375 24.703125 32.125 29.90625 \nQ 28.265625 35.109375 21.484375 37.9375 \nQ 16.15625 40.140625 6.984375 40.484375 \nL 19.671875 66.21875 \nz\n\" id=\"TimesNewRomanPSMT-35\"/>\n     <path d=\"M 12.5 9.46875 \nQ 14.796875 9.46875 16.359375 7.875 \nQ 17.921875 6.296875 17.921875 4.046875 \nQ 17.921875 1.8125 16.328125 0.21875 \nQ 14.75 -1.375 12.5 -1.375 \nQ 10.25 -1.375 8.65625 0.21875 \nQ 7.078125 1.8125 7.078125 4.046875 \nQ 7.078125 6.34375 8.65625 7.90625 \nQ 10.25 9.46875 12.5 9.46875 \nz\n\" id=\"TimesNewRomanPSMT-2e\"/>\n     <path d=\"M 45.84375 12.75 \nL 41.21875 0 \nL 2.15625 0 \nL 2.15625 1.8125 \nQ 19.390625 17.53125 26.421875 27.484375 \nQ 33.453125 37.453125 33.453125 45.703125 \nQ 33.453125 52 29.59375 56.046875 \nQ 25.734375 60.109375 20.359375 60.109375 \nQ 15.484375 60.109375 11.59375 57.25 \nQ 7.71875 54.390625 5.859375 48.875 \nL 4.046875 48.875 \nQ 5.28125 57.90625 10.328125 62.734375 \nQ 15.375 67.578125 22.953125 67.578125 \nQ 31 67.578125 36.390625 62.40625 \nQ 41.796875 57.234375 41.796875 50.203125 \nQ 41.796875 45.171875 39.453125 40.140625 \nQ 35.84375 32.234375 27.734375 23.390625 \nQ 15.578125 10.109375 12.546875 7.375 \nL 29.828125 7.375 \nQ 35.109375 7.375 37.234375 7.765625 \nQ 39.359375 8.15625 41.0625 9.34375 \nQ 42.78125 10.546875 44.046875 12.75 \nz\n\" id=\"TimesNewRomanPSMT-32\"/>\n     <path d=\"M 67.96875 67.71875 \nL 19.734375 -2.734375 \nL 15.375 -2.734375 \nL 63.625 67.71875 \nz\nM 17.78125 67.71875 \nQ 24.359375 67.71875 28 62.25 \nQ 31.640625 56.78125 31.640625 49.703125 \nQ 31.640625 41.21875 27.53125 36.578125 \nQ 23.4375 31.9375 17.671875 31.9375 \nQ 13.8125 31.9375 10.59375 34.0625 \nQ 7.375 36.1875 5.4375 40.375 \nQ 3.515625 44.578125 3.515625 49.703125 \nQ 3.515625 54.828125 5.46875 59.15625 \nQ 7.421875 63.484375 10.8125 65.59375 \nQ 14.203125 67.71875 17.78125 67.71875 \nz\nM 17.625 64.984375 \nQ 15.140625 64.984375 13.203125 62.046875 \nQ 11.28125 59.125 11.28125 49.75 \nQ 11.28125 42.96875 12.359375 39.40625 \nQ 13.1875 36.71875 14.9375 35.25 \nQ 15.96875 34.375 17.484375 34.375 \nQ 19.828125 34.375 21.484375 36.921875 \nQ 23.921875 40.671875 23.921875 49.46875 \nQ 23.921875 58.734375 21.53125 62.5 \nQ 19.96875 64.984375 17.625 64.984375 \nz\nM 65.71875 32.859375 \nQ 69.1875 32.859375 72.625 30.65625 \nQ 76.078125 28.46875 77.953125 24.265625 \nQ 79.828125 20.0625 79.828125 15.046875 \nQ 79.828125 6.390625 75.671875 1.828125 \nQ 71.53125 -2.734375 65.875 -2.734375 \nQ 62.3125 -2.734375 58.953125 -0.53125 \nQ 55.609375 1.65625 53.6875 5.734375 \nQ 51.765625 9.8125 51.765625 15.046875 \nQ 51.765625 20.171875 53.6875 24.40625 \nQ 55.609375 28.65625 58.953125 30.75 \nQ 62.3125 32.859375 65.71875 32.859375 \nz\nM 65.765625 30.28125 \nQ 63.421875 30.28125 61.71875 27.640625 \nQ 59.515625 24.21875 59.515625 14.703125 \nQ 59.515625 5.953125 61.765625 2.484375 \nQ 63.421875 0 65.765625 0 \nQ 68.015625 0 69.78125 2.6875 \nQ 72.125 6.25 72.125 14.9375 \nQ 72.125 24.125 69.78125 27.78125 \nQ 68.171875 30.28125 65.765625 30.28125 \nz\n\" id=\"TimesNewRomanPSMT-25\"/>\n     <path id=\"TimesNewRomanPSMT-20\"/>\n     <path d=\"M 31.0625 -19.578125 \nL 31.0625 -21.390625 \nQ 23.6875 -17.671875 18.75 -12.703125 \nQ 11.71875 -5.609375 7.90625 4 \nQ 4.109375 13.625 4.109375 23.96875 \nQ 4.109375 39.109375 11.578125 51.578125 \nQ 19.046875 64.0625 31.0625 69.4375 \nL 31.0625 67.390625 \nQ 25.046875 64.0625 21.1875 58.296875 \nQ 17.328125 52.546875 15.421875 43.703125 \nQ 13.53125 34.859375 13.53125 25.25 \nQ 13.53125 14.796875 15.140625 6.25 \nQ 16.40625 -0.484375 18.203125 -4.5625 \nQ 20.015625 -8.640625 23.0625 -12.390625 \nQ 26.125 -16.15625 31.0625 -19.578125 \nz\n\" id=\"TimesNewRomanPSMT-28\"/>\n     <path d=\"M 10.0625 66.21875 \nL 45.5625 66.21875 \nL 45.5625 64.359375 \nL 23.484375 -1.375 \nL 18.015625 -1.375 \nL 37.796875 58.25 \nL 19.578125 58.25 \nQ 14.0625 58.25 11.71875 56.9375 \nQ 7.625 54.6875 5.125 50 \nL 3.71875 50.53125 \nz\n\" id=\"TimesNewRomanPSMT-37\"/>\n     <path d=\"M 5.28125 -1.375 \nL 5.28125 0.4375 \nQ 11.625 0.53125 17.09375 3.390625 \nQ 22.5625 6.25 27.65625 13.375 \nQ 32.765625 20.515625 34.765625 29.046875 \nQ 27.09375 24.125 20.90625 24.125 \nQ 13.921875 24.125 8.9375 29.515625 \nQ 3.953125 34.90625 3.953125 43.84375 \nQ 3.953125 52.546875 8.9375 59.328125 \nQ 14.9375 67.578125 24.609375 67.578125 \nQ 32.765625 67.578125 38.578125 60.84375 \nQ 45.703125 52.484375 45.703125 40.234375 \nQ 45.703125 29.203125 40.28125 19.65625 \nQ 34.859375 10.109375 25.203125 3.8125 \nQ 17.328125 -1.375 8.0625 -1.375 \nz\nM 35.546875 32.671875 \nQ 36.421875 39.015625 36.421875 42.828125 \nQ 36.421875 47.5625 34.8125 53.046875 \nQ 33.203125 58.546875 30.25 61.46875 \nQ 27.296875 64.40625 23.53125 64.40625 \nQ 19.1875 64.40625 15.90625 60.5 \nQ 12.640625 56.59375 12.640625 48.875 \nQ 12.640625 38.578125 17 32.765625 \nQ 20.171875 28.5625 24.8125 28.5625 \nQ 27.046875 28.5625 30.125 29.640625 \nQ 33.203125 30.71875 35.546875 32.671875 \nz\n\" id=\"TimesNewRomanPSMT-39\"/>\n     <path d=\"M 2.25 67.390625 \nL 2.25 69.4375 \nQ 9.671875 65.765625 14.59375 60.796875 \nQ 21.578125 53.65625 25.390625 44.0625 \nQ 29.203125 34.46875 29.203125 24.078125 \nQ 29.203125 8.9375 21.75 -3.53125 \nQ 14.3125 -16.015625 2.25 -21.390625 \nL 2.25 -19.578125 \nQ 8.25 -16.21875 12.125 -10.46875 \nQ 16.015625 -4.734375 17.890625 4.125 \nQ 19.78125 12.984375 19.78125 22.609375 \nQ 19.78125 33.015625 18.171875 41.609375 \nQ 16.9375 48.34375 15.109375 52.390625 \nQ 13.28125 56.453125 10.25 60.203125 \nQ 7.234375 63.96875 2.25 67.390625 \nz\n\" id=\"TimesNewRomanPSMT-29\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(119.141852 103.87581)scale(0.14 -0.14)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-35\"/>\n     <use x=\"50\" xlink:href=\"#TimesNewRomanPSMT-35\"/>\n     <use x=\"100\" xlink:href=\"#TimesNewRomanPSMT-2e\"/>\n     <use x=\"125\" xlink:href=\"#TimesNewRomanPSMT-32\"/>\n     <use x=\"175\" xlink:href=\"#TimesNewRomanPSMT-32\"/>\n     <use x=\"225\" xlink:href=\"#TimesNewRomanPSMT-25\"/>\n     <use x=\"308.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"333.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"358.300781\" xlink:href=\"#TimesNewRomanPSMT-28\"/>\n     <use x=\"391.601562\" xlink:href=\"#TimesNewRomanPSMT-37\"/>\n     <use x=\"441.601562\" xlink:href=\"#TimesNewRomanPSMT-39\"/>\n     <use x=\"491.601562\" xlink:href=\"#TimesNewRomanPSMT-39\"/>\n     <use x=\"541.601562\" xlink:href=\"#TimesNewRomanPSMT-29\"/>\n    </g>\n   </g>\n   <g id=\"text_3\">\n    <!-- Success -->\n    <defs>\n     <path d=\"M 45.84375 67.71875 \nL 45.84375 44.828125 \nL 44.046875 44.828125 \nQ 43.171875 51.421875 40.890625 55.328125 \nQ 38.625 59.234375 34.421875 61.515625 \nQ 30.21875 63.8125 25.734375 63.8125 \nQ 20.65625 63.8125 17.328125 60.71875 \nQ 14.015625 57.625 14.015625 53.65625 \nQ 14.015625 50.640625 16.109375 48.140625 \nQ 19.140625 44.484375 30.515625 38.375 \nQ 39.796875 33.40625 43.1875 30.734375 \nQ 46.578125 28.078125 48.40625 24.453125 \nQ 50.25 20.84375 50.25 16.890625 \nQ 50.25 9.375 44.40625 3.921875 \nQ 38.578125 -1.515625 29.390625 -1.515625 \nQ 26.515625 -1.515625 23.96875 -1.078125 \nQ 22.46875 -0.828125 17.703125 0.703125 \nQ 12.9375 2.25 11.671875 2.25 \nQ 10.453125 2.25 9.734375 1.515625 \nQ 9.03125 0.78125 8.6875 -1.515625 \nL 6.890625 -1.515625 \nL 6.890625 21.1875 \nL 8.6875 21.1875 \nQ 9.96875 14.0625 12.109375 10.515625 \nQ 14.265625 6.984375 18.671875 4.640625 \nQ 23.09375 2.296875 28.375 2.296875 \nQ 34.46875 2.296875 38 5.515625 \nQ 41.546875 8.734375 41.546875 13.140625 \nQ 41.546875 15.578125 40.203125 18.0625 \nQ 38.875 20.5625 36.03125 22.703125 \nQ 34.125 24.171875 25.625 28.921875 \nQ 17.140625 33.6875 13.546875 36.515625 \nQ 9.96875 39.359375 8.109375 42.765625 \nQ 6.25 46.1875 6.25 50.296875 \nQ 6.25 57.421875 11.71875 62.5625 \nQ 17.1875 67.71875 25.640625 67.71875 \nQ 30.90625 67.71875 36.8125 65.140625 \nQ 39.546875 63.921875 40.671875 63.921875 \nQ 41.9375 63.921875 42.75 64.671875 \nQ 43.5625 65.4375 44.046875 67.71875 \nz\n\" id=\"TimesNewRomanPSMT-53\"/>\n     <path d=\"M 42.328125 44.734375 \nL 42.328125 17.625 \nQ 42.328125 9.859375 42.6875 8.125 \nQ 43.0625 6.390625 43.859375 5.703125 \nQ 44.671875 5.03125 45.75 5.03125 \nQ 47.265625 5.03125 49.171875 5.859375 \nL 49.859375 4.15625 \nL 36.46875 -1.375 \nL 34.28125 -1.375 \nL 34.28125 8.109375 \nQ 28.515625 1.859375 25.484375 0.234375 \nQ 22.46875 -1.375 19.09375 -1.375 \nQ 15.328125 -1.375 12.5625 0.796875 \nQ 9.8125 2.984375 8.734375 6.390625 \nQ 7.671875 9.8125 7.671875 16.0625 \nL 7.671875 36.03125 \nQ 7.671875 39.203125 6.984375 40.421875 \nQ 6.296875 41.65625 4.953125 42.3125 \nQ 3.609375 42.96875 0.09375 42.921875 \nL 0.09375 44.734375 \nL 15.765625 44.734375 \nL 15.765625 14.796875 \nQ 15.765625 8.546875 17.9375 6.59375 \nQ 20.125 4.640625 23.1875 4.640625 \nQ 25.296875 4.640625 27.953125 5.953125 \nQ 30.609375 7.28125 34.28125 10.984375 \nL 34.28125 36.328125 \nQ 34.28125 40.140625 32.890625 41.484375 \nQ 31.5 42.828125 27.09375 42.921875 \nL 27.09375 44.734375 \nz\n\" id=\"TimesNewRomanPSMT-75\"/>\n     <path d=\"M 41.109375 17 \nQ 39.3125 8.15625 34.03125 3.390625 \nQ 28.765625 -1.375 22.359375 -1.375 \nQ 14.75 -1.375 9.078125 5.015625 \nQ 3.421875 11.421875 3.421875 22.3125 \nQ 3.421875 32.859375 9.6875 39.453125 \nQ 15.96875 46.046875 24.75 46.046875 \nQ 31.34375 46.046875 35.59375 42.546875 \nQ 39.84375 39.0625 39.84375 35.296875 \nQ 39.84375 33.453125 38.640625 32.296875 \nQ 37.453125 31.15625 35.296875 31.15625 \nQ 32.421875 31.15625 30.953125 33.015625 \nQ 30.125 34.03125 29.859375 36.90625 \nQ 29.59375 39.796875 27.875 41.3125 \nQ 26.171875 42.78125 23.140625 42.78125 \nQ 18.265625 42.78125 15.28125 39.15625 \nQ 11.328125 34.375 11.328125 26.515625 \nQ 11.328125 18.5 15.25 12.375 \nQ 19.1875 6.25 25.875 6.25 \nQ 30.671875 6.25 34.46875 9.515625 \nQ 37.15625 11.765625 39.703125 17.671875 \nz\n\" id=\"TimesNewRomanPSMT-63\"/>\n     <path d=\"M 10.640625 27.875 \nQ 10.59375 17.921875 15.484375 12.25 \nQ 20.359375 6.59375 26.953125 6.59375 \nQ 31.34375 6.59375 34.59375 9 \nQ 37.84375 11.421875 40.046875 17.28125 \nL 41.546875 16.3125 \nQ 40.53125 9.625 35.59375 4.125 \nQ 30.671875 -1.375 23.25 -1.375 \nQ 15.1875 -1.375 9.453125 4.90625 \nQ 3.71875 11.1875 3.71875 21.78125 \nQ 3.71875 33.25 9.59375 39.671875 \nQ 15.484375 46.09375 24.359375 46.09375 \nQ 31.890625 46.09375 36.71875 41.140625 \nQ 41.546875 36.1875 41.546875 27.875 \nz\nM 10.640625 30.71875 \nL 31.34375 30.71875 \nQ 31.109375 35.015625 30.328125 36.765625 \nQ 29.109375 39.5 26.6875 41.0625 \nQ 24.265625 42.625 21.625 42.625 \nQ 17.578125 42.625 14.375 39.46875 \nQ 11.1875 36.328125 10.640625 30.71875 \nz\n\" id=\"TimesNewRomanPSMT-65\"/>\n     <path d=\"M 32.03125 46.046875 \nL 32.03125 30.8125 \nL 30.421875 30.8125 \nQ 28.5625 37.984375 25.65625 40.578125 \nQ 22.75 43.171875 18.265625 43.171875 \nQ 14.84375 43.171875 12.734375 41.359375 \nQ 10.640625 39.546875 10.640625 37.359375 \nQ 10.640625 34.625 12.203125 32.671875 \nQ 13.71875 30.671875 18.359375 28.421875 \nL 25.484375 24.953125 \nQ 35.40625 20.125 35.40625 12.203125 \nQ 35.40625 6.109375 30.78125 2.359375 \nQ 26.171875 -1.375 20.453125 -1.375 \nQ 16.359375 -1.375 11.078125 0.09375 \nQ 9.46875 0.59375 8.453125 0.59375 \nQ 7.328125 0.59375 6.6875 -0.6875 \nL 5.078125 -0.6875 \nL 5.078125 15.28125 \nL 6.6875 15.28125 \nQ 8.0625 8.453125 11.90625 4.984375 \nQ 15.765625 1.515625 20.5625 1.515625 \nQ 23.921875 1.515625 26.046875 3.484375 \nQ 28.171875 5.46875 28.171875 8.25 \nQ 28.171875 11.625 25.796875 13.921875 \nQ 23.4375 16.21875 16.359375 19.734375 \nQ 9.28125 23.25 7.078125 26.078125 \nQ 4.890625 28.859375 4.890625 33.109375 \nQ 4.890625 38.625 8.671875 42.328125 \nQ 12.453125 46.046875 18.453125 46.046875 \nQ 21.09375 46.046875 24.859375 44.921875 \nQ 27.34375 44.1875 28.171875 44.1875 \nQ 28.953125 44.1875 29.390625 44.53125 \nQ 29.828125 44.875 30.421875 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-73\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(292.569864 218.543121)scale(0.16 -0.16)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-53\"/>\n     <use x=\"55.615234\" xlink:href=\"#TimesNewRomanPSMT-75\"/>\n     <use x=\"105.615234\" xlink:href=\"#TimesNewRomanPSMT-63\"/>\n     <use x=\"150\" xlink:href=\"#TimesNewRomanPSMT-63\"/>\n     <use x=\"194.384766\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"238.769531\" xlink:href=\"#TimesNewRomanPSMT-73\"/>\n     <use x=\"277.685547\" xlink:href=\"#TimesNewRomanPSMT-73\"/>\n    </g>\n   </g>\n   <g id=\"text_4\">\n    <!-- 44.78%  (648) -->\n    <defs>\n     <path d=\"M 46.53125 24.421875 \nL 46.53125 17.484375 \nL 37.640625 17.484375 \nL 37.640625 0 \nL 29.59375 0 \nL 29.59375 17.484375 \nL 1.5625 17.484375 \nL 1.5625 23.734375 \nL 32.28125 67.578125 \nL 37.640625 67.578125 \nL 37.640625 24.421875 \nz\nM 29.59375 24.421875 \nL 29.59375 57.28125 \nL 6.34375 24.421875 \nz\n\" id=\"TimesNewRomanPSMT-34\"/>\n     <path d=\"M 19.1875 33.34375 \nQ 11.328125 39.796875 9.046875 43.703125 \nQ 6.78125 47.609375 6.78125 51.8125 \nQ 6.78125 58.25 11.765625 62.90625 \nQ 16.75 67.578125 25 67.578125 \nQ 33.015625 67.578125 37.890625 63.234375 \nQ 42.78125 58.890625 42.78125 53.328125 \nQ 42.78125 49.609375 40.140625 45.75 \nQ 37.5 41.890625 29.15625 36.671875 \nQ 37.75 30.03125 40.53125 26.21875 \nQ 44.234375 21.234375 44.234375 15.71875 \nQ 44.234375 8.734375 38.90625 3.78125 \nQ 33.59375 -1.171875 24.953125 -1.171875 \nQ 15.53125 -1.171875 10.25 4.734375 \nQ 6.0625 9.46875 6.0625 15.09375 \nQ 6.0625 19.484375 9.015625 23.796875 \nQ 11.96875 28.125 19.1875 33.34375 \nz\nM 26.859375 38.578125 \nQ 32.71875 43.84375 34.28125 46.890625 \nQ 35.84375 49.953125 35.84375 53.8125 \nQ 35.84375 58.9375 32.953125 61.84375 \nQ 30.078125 64.75 25.09375 64.75 \nQ 20.125 64.75 17 61.859375 \nQ 13.875 58.984375 13.875 55.125 \nQ 13.875 52.59375 15.15625 50.046875 \nQ 16.453125 47.515625 18.84375 45.21875 \nz\nM 21.484375 31.5 \nQ 17.4375 28.078125 15.484375 24.046875 \nQ 13.53125 20.015625 13.53125 15.328125 \nQ 13.53125 9.03125 16.96875 5.25 \nQ 20.40625 1.46875 25.734375 1.46875 \nQ 31 1.46875 34.171875 4.4375 \nQ 37.359375 7.421875 37.359375 11.671875 \nQ 37.359375 15.1875 35.5 17.96875 \nQ 32.03125 23.140625 21.484375 31.5 \nz\n\" id=\"TimesNewRomanPSMT-38\"/>\n     <path d=\"M 44.828125 67.578125 \nL 44.828125 65.765625 \nQ 38.375 65.140625 34.296875 63.203125 \nQ 30.21875 61.28125 26.234375 57.328125 \nQ 22.265625 53.375 19.65625 48.515625 \nQ 17.046875 43.65625 15.28125 36.96875 \nQ 22.3125 41.796875 29.390625 41.796875 \nQ 36.1875 41.796875 41.15625 36.328125 \nQ 46.140625 30.859375 46.140625 22.265625 \nQ 46.140625 13.96875 41.109375 7.125 \nQ 35.0625 -1.171875 25.09375 -1.171875 \nQ 18.3125 -1.171875 13.578125 3.328125 \nQ 4.296875 12.0625 4.296875 25.984375 \nQ 4.296875 34.859375 7.859375 42.859375 \nQ 11.421875 50.875 18.03125 57.078125 \nQ 24.65625 63.28125 30.703125 65.421875 \nQ 36.765625 67.578125 42 67.578125 \nz\nM 14.453125 33.40625 \nQ 13.578125 26.8125 13.578125 22.75 \nQ 13.578125 18.0625 15.3125 12.5625 \nQ 17.046875 7.078125 20.453125 3.859375 \nQ 22.953125 1.5625 26.515625 1.5625 \nQ 30.765625 1.5625 34.109375 5.5625 \nQ 37.453125 9.578125 37.453125 17 \nQ 37.453125 25.34375 34.125 31.4375 \nQ 30.8125 37.546875 24.703125 37.546875 \nQ 22.859375 37.546875 20.734375 36.765625 \nQ 18.609375 35.984375 14.453125 33.40625 \nz\n\" id=\"TimesNewRomanPSMT-36\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(213.155266 184.478286)scale(0.14 -0.14)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-34\"/>\n     <use x=\"50\" xlink:href=\"#TimesNewRomanPSMT-34\"/>\n     <use x=\"100\" xlink:href=\"#TimesNewRomanPSMT-2e\"/>\n     <use x=\"125\" xlink:href=\"#TimesNewRomanPSMT-37\"/>\n     <use x=\"175\" xlink:href=\"#TimesNewRomanPSMT-38\"/>\n     <use x=\"225\" xlink:href=\"#TimesNewRomanPSMT-25\"/>\n     <use x=\"308.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"333.300781\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"358.300781\" xlink:href=\"#TimesNewRomanPSMT-28\"/>\n     <use x=\"391.601562\" xlink:href=\"#TimesNewRomanPSMT-36\"/>\n     <use x=\"441.601562\" xlink:href=\"#TimesNewRomanPSMT-34\"/>\n     <use x=\"491.601562\" xlink:href=\"#TimesNewRomanPSMT-38\"/>\n     <use x=\"541.601562\" xlink:href=\"#TimesNewRomanPSMT-29\"/>\n    </g>\n   </g>\n   <g id=\"text_5\">\n    <!-- Rerun rate per dataset -->\n    <defs>\n     <path d=\"M 67.578125 0 \nL 49.90625 0 \nL 27.484375 30.953125 \nQ 25 30.859375 23.4375 30.859375 \nQ 22.796875 30.859375 22.0625 30.875 \nQ 21.34375 30.90625 20.5625 30.953125 \nL 20.5625 11.71875 \nQ 20.5625 5.46875 21.921875 3.953125 \nQ 23.78125 1.8125 27.484375 1.8125 \nL 30.078125 1.8125 \nL 30.078125 0 \nL 1.703125 0 \nL 1.703125 1.8125 \nL 4.203125 1.8125 \nQ 8.40625 1.8125 10.203125 4.546875 \nQ 11.234375 6.0625 11.234375 11.71875 \nL 11.234375 54.5 \nQ 11.234375 60.75 9.859375 62.25 \nQ 7.953125 64.40625 4.203125 64.40625 \nL 1.703125 64.40625 \nL 1.703125 66.21875 \nL 25.828125 66.21875 \nQ 36.375 66.21875 41.375 64.671875 \nQ 46.390625 63.140625 49.875 59.015625 \nQ 53.375 54.890625 53.375 49.171875 \nQ 53.375 43.0625 49.390625 38.5625 \nQ 45.40625 34.078125 37.0625 32.234375 \nL 50.734375 13.234375 \nQ 55.421875 6.6875 58.78125 4.53125 \nQ 62.15625 2.390625 67.578125 1.8125 \nz\nM 20.5625 34.03125 \nQ 21.484375 34.03125 22.171875 34 \nQ 22.859375 33.984375 23.296875 33.984375 \nQ 32.765625 33.984375 37.578125 38.078125 \nQ 42.390625 42.1875 42.390625 48.53125 \nQ 42.390625 54.734375 38.5 58.609375 \nQ 34.625 62.5 28.21875 62.5 \nQ 25.390625 62.5 20.5625 61.578125 \nz\n\" id=\"TimesNewRomanPSMT-52\"/>\n     <path d=\"M 16.15625 36.578125 \nQ 24.03125 46.046875 31.15625 46.046875 \nQ 34.8125 46.046875 37.453125 44.21875 \nQ 40.09375 42.390625 41.65625 38.1875 \nQ 42.71875 35.25 42.71875 29.203125 \nL 42.71875 10.109375 \nQ 42.71875 5.859375 43.40625 4.34375 \nQ 43.953125 3.125 45.140625 2.4375 \nQ 46.34375 1.765625 49.5625 1.765625 \nL 49.5625 0 \nL 27.4375 0 \nL 27.4375 1.765625 \nL 28.375 1.765625 \nQ 31.5 1.765625 32.734375 2.703125 \nQ 33.984375 3.65625 34.46875 5.515625 \nQ 34.671875 6.25 34.671875 10.109375 \nL 34.671875 28.421875 \nQ 34.671875 34.515625 33.078125 37.28125 \nQ 31.5 40.046875 27.734375 40.046875 \nQ 21.921875 40.046875 16.15625 33.6875 \nL 16.15625 10.109375 \nQ 16.15625 5.5625 16.703125 4.5 \nQ 17.390625 3.078125 18.578125 2.421875 \nQ 19.78125 1.765625 23.4375 1.765625 \nL 23.4375 0 \nL 1.3125 0 \nL 1.3125 1.765625 \nL 2.296875 1.765625 \nQ 5.71875 1.765625 6.90625 3.484375 \nQ 8.109375 5.21875 8.109375 10.109375 \nL 8.109375 26.703125 \nQ 8.109375 34.765625 7.734375 36.515625 \nQ 7.375 38.28125 6.609375 38.90625 \nQ 5.859375 39.546875 4.59375 39.546875 \nQ 3.21875 39.546875 1.3125 38.8125 \nL 0.59375 40.578125 \nL 14.0625 46.046875 \nL 16.15625 46.046875 \nz\n\" id=\"TimesNewRomanPSMT-6e\"/>\n     <path d=\"M 28.46875 6.453125 \nQ 21.578125 1.125 19.828125 0.296875 \nQ 17.1875 -0.921875 14.203125 -0.921875 \nQ 9.578125 -0.921875 6.5625 2.25 \nQ 3.5625 5.421875 3.5625 10.59375 \nQ 3.5625 13.875 5.03125 16.265625 \nQ 7.03125 19.578125 11.984375 22.5 \nQ 16.9375 25.4375 28.46875 29.640625 \nL 28.46875 31.390625 \nQ 28.46875 38.09375 26.34375 40.578125 \nQ 24.21875 43.0625 20.171875 43.0625 \nQ 17.09375 43.0625 15.28125 41.40625 \nQ 13.421875 39.75 13.421875 37.59375 \nL 13.53125 34.765625 \nQ 13.53125 32.515625 12.375 31.296875 \nQ 11.234375 30.078125 9.375 30.078125 \nQ 7.5625 30.078125 6.421875 31.34375 \nQ 5.28125 32.625 5.28125 34.8125 \nQ 5.28125 39.015625 9.578125 42.53125 \nQ 13.875 46.046875 21.625 46.046875 \nQ 27.59375 46.046875 31.390625 44.046875 \nQ 34.28125 42.53125 35.640625 39.3125 \nQ 36.53125 37.203125 36.53125 30.71875 \nL 36.53125 15.53125 \nQ 36.53125 9.125 36.765625 7.6875 \nQ 37.015625 6.25 37.578125 5.765625 \nQ 38.140625 5.28125 38.875 5.28125 \nQ 39.65625 5.28125 40.234375 5.609375 \nQ 41.265625 6.25 44.1875 9.1875 \nL 44.1875 6.453125 \nQ 38.71875 -0.875 33.734375 -0.875 \nQ 31.34375 -0.875 29.921875 0.78125 \nQ 28.515625 2.4375 28.46875 6.453125 \nz\nM 28.46875 9.625 \nL 28.46875 26.65625 \nQ 21.09375 23.734375 18.953125 22.515625 \nQ 15.09375 20.359375 13.421875 18.015625 \nQ 11.765625 15.671875 11.765625 12.890625 \nQ 11.765625 9.375 13.859375 7.046875 \nQ 15.96875 4.734375 18.703125 4.734375 \nQ 22.40625 4.734375 28.46875 9.625 \nz\n\" id=\"TimesNewRomanPSMT-61\"/>\n     <path d=\"M 16.109375 59.421875 \nL 16.109375 44.734375 \nL 26.5625 44.734375 \nL 26.5625 41.3125 \nL 16.109375 41.3125 \nL 16.109375 12.3125 \nQ 16.109375 7.953125 17.359375 6.4375 \nQ 18.609375 4.9375 20.5625 4.9375 \nQ 22.171875 4.9375 23.6875 5.9375 \nQ 25.203125 6.9375 26.03125 8.890625 \nL 27.9375 8.890625 \nQ 26.21875 4.109375 23.09375 1.6875 \nQ 19.96875 -0.734375 16.65625 -0.734375 \nQ 14.40625 -0.734375 12.25 0.515625 \nQ 10.109375 1.765625 9.078125 4.078125 \nQ 8.0625 6.390625 8.0625 11.234375 \nL 8.0625 41.3125 \nL 0.984375 41.3125 \nL 0.984375 42.921875 \nQ 3.65625 44 6.46875 46.5625 \nQ 9.28125 49.125 11.46875 52.640625 \nQ 12.59375 54.5 14.59375 59.421875 \nz\n\" id=\"TimesNewRomanPSMT-74\"/>\n     <path d=\"M -0.09375 40.28125 \nL 13.671875 45.84375 \nL 15.53125 45.84375 \nL 15.53125 35.40625 \nQ 19 41.3125 22.484375 43.671875 \nQ 25.984375 46.046875 29.828125 46.046875 \nQ 36.578125 46.046875 41.0625 40.765625 \nQ 46.578125 34.328125 46.578125 23.96875 \nQ 46.578125 12.40625 39.9375 4.828125 \nQ 34.46875 -1.375 26.171875 -1.375 \nQ 22.5625 -1.375 19.921875 -0.34375 \nQ 17.96875 0.390625 15.53125 2.59375 \nL 15.53125 -11.03125 \nQ 15.53125 -15.625 16.09375 -16.859375 \nQ 16.65625 -18.109375 18.046875 -18.84375 \nQ 19.4375 -19.578125 23.09375 -19.578125 \nL 23.09375 -21.390625 \nL -0.34375 -21.390625 \nL -0.34375 -19.578125 \nL 0.875 -19.578125 \nQ 3.5625 -19.625 5.46875 -18.5625 \nQ 6.390625 -18.015625 6.90625 -16.8125 \nQ 7.421875 -15.625 7.421875 -10.75 \nL 7.421875 31.546875 \nQ 7.421875 35.890625 7.03125 37.0625 \nQ 6.640625 38.234375 5.78125 38.8125 \nQ 4.9375 39.40625 3.46875 39.40625 \nQ 2.296875 39.40625 0.484375 38.71875 \nz\nM 15.53125 32.515625 \nL 15.53125 15.828125 \nQ 15.53125 10.40625 15.96875 8.6875 \nQ 16.65625 5.859375 19.3125 3.703125 \nQ 21.96875 1.5625 26.03125 1.5625 \nQ 30.90625 1.5625 33.9375 5.375 \nQ 37.890625 10.359375 37.890625 19.390625 \nQ 37.890625 29.640625 33.40625 35.15625 \nQ 30.28125 38.96875 25.984375 38.96875 \nQ 23.640625 38.96875 21.34375 37.796875 \nQ 19.578125 36.921875 15.53125 32.515625 \nz\n\" id=\"TimesNewRomanPSMT-70\"/>\n     <path d=\"M 34.71875 5.03125 \nQ 31.453125 1.609375 28.328125 0.109375 \nQ 25.203125 -1.375 21.578125 -1.375 \nQ 14.265625 -1.375 8.796875 4.75 \nQ 3.328125 10.890625 3.328125 20.515625 \nQ 3.328125 30.125 9.375 38.109375 \nQ 15.4375 46.09375 24.953125 46.09375 \nQ 30.859375 46.09375 34.71875 42.328125 \nL 34.71875 50.59375 \nQ 34.71875 58.25 34.34375 60 \nQ 33.984375 61.765625 33.203125 62.390625 \nQ 32.421875 63.03125 31.25 63.03125 \nQ 29.984375 63.03125 27.875 62.25 \nL 27.25 63.96875 \nL 40.578125 69.4375 \nL 42.78125 69.4375 \nL 42.78125 17.71875 \nQ 42.78125 9.859375 43.140625 8.125 \nQ 43.5 6.390625 44.3125 5.703125 \nQ 45.125 5.03125 46.1875 5.03125 \nQ 47.515625 5.03125 49.703125 5.859375 \nL 50.25 4.15625 \nL 36.96875 -1.375 \nL 34.71875 -1.375 \nz\nM 34.71875 8.453125 \nL 34.71875 31.5 \nQ 34.421875 34.8125 32.953125 37.546875 \nQ 31.5 40.28125 29.078125 41.671875 \nQ 26.65625 43.0625 24.359375 43.0625 \nQ 20.0625 43.0625 16.703125 39.203125 \nQ 12.25 34.125 12.25 24.359375 \nQ 12.25 14.5 16.546875 9.25 \nQ 20.84375 4 26.125 4 \nQ 30.5625 4 34.71875 8.453125 \nz\n\" id=\"TimesNewRomanPSMT-64\"/>\n    </defs>\n    <g style=\"fill:#262626;\" transform=\"translate(118.460625 21.0875)scale(0.2 -0.2)\">\n     <use xlink:href=\"#TimesNewRomanPSMT-52\"/>\n     <use x=\"66.699219\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"111.083984\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"144.384766\" xlink:href=\"#TimesNewRomanPSMT-75\"/>\n     <use x=\"194.384766\" xlink:href=\"#TimesNewRomanPSMT-6e\"/>\n     <use x=\"244.384766\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"269.384766\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"302.685547\" xlink:href=\"#TimesNewRomanPSMT-61\"/>\n     <use x=\"347.070312\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n     <use x=\"374.853516\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"419.238281\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"444.238281\" xlink:href=\"#TimesNewRomanPSMT-70\"/>\n     <use x=\"494.238281\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"538.623047\" xlink:href=\"#TimesNewRomanPSMT-72\"/>\n     <use x=\"571.923828\" xlink:href=\"#TimesNewRomanPSMT-20\"/>\n     <use x=\"596.923828\" xlink:href=\"#TimesNewRomanPSMT-64\"/>\n     <use x=\"646.923828\" xlink:href=\"#TimesNewRomanPSMT-61\"/>\n     <use x=\"691.308594\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n     <use x=\"719.091797\" xlink:href=\"#TimesNewRomanPSMT-61\"/>\n     <use x=\"763.476562\" xlink:href=\"#TimesNewRomanPSMT-73\"/>\n     <use x=\"802.392578\" xlink:href=\"#TimesNewRomanPSMT-65\"/>\n     <use x=\"846.777344\" xlink:href=\"#TimesNewRomanPSMT-74\"/>\n    </g>\n   </g>\n  </g>\n </g>\n <defs>\n  <clipPath id=\"p2ee97d3736\">\n   <rect height=\"229.94\" width=\"390.44\" x=\"10.7\" y=\"27.0875\"/>\n  </clipPath>\n </defs>\n</svg>\n",
      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sizes = [len(ag_tot)-len(ag_suc), len(ag_suc)]\n",
    "plot_code(sizes, \"Rerun rate per dataset\", \"dataset_rate.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "env",
   "language": "python",
   "name": "env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "3.7.3-final"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}